Lakeview Loan Servicing

Role Description The Insurance Sales Agent is a high-performing, commission-driven sales professional with a proven track record of success in fast-paced, call center sales environments. Agents will be responsible for writing only personal lines insurance products such as home, auto, umbrella, and flood through our carrier partners. This position is fully remote which requires reliable, high-speed internet and a dedicated workspace, free of distractions. Responsibilities - Conduct outbound sales calls to potential prospects utilizing a lead management system. - Handle inbound sales calls through an ACD phone system. - Cross-sell other lines of business 100% of the time. - Quote home and auto policies through a rating system. - Successfully navigate carrier websites to finalize quotes and bind policies. - Manage client interactions and follow-up within the designated software systems. Qualifications - Strong communication, sales, and prospecting skills. - Proficient in Microsoft Office Suite of products. - Ability to learn new systems quickly; experience with comparative raters is a plus. - Working knowledge of the insurance industry. - Must be detail-oriented and results-driven with a focus on customer service. - High School diploma required. - 2+ years of Property and Casualty Insurance Sales experience preferred. - Call center experience a plus but not required. Requirements - Active Property & Casualty Insurance License issued by the Department of Insurance of the employee’s resident state. Physical Demands and Work Environment - Regular sitting and use of hands for handling objects, tools, or controls. - Frequent talking and listening in a moderately noisy environment. - Occasional standing, walking, and reaching with hands and arms. - Rare instances of stooping, kneeling, crouching, or crawling. - Lifting and moving objects up to 10 pounds is a regular part of the role. - Specific vision abilities such as close vision, color vision, and the ability to adjust focus are necessary. - Must connect to the internet via a direct Ethernet connection. - Maintain a dedicated workspace to safeguard customer information. - Internet connection with a minimum download speed of 50 Mbps and a minimum upload speed of 10 Mbps is required. - If using shared internet, prioritizing the connection for work purposes is strongly recommended. EEOC Lakeview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law. #LI-Remote

Role Description We are seeking a highly motivated Contract Technical Recruiter to support hiring for a new startup product initiative within our organization. This role will play a critical part in building a multi-disciplinary team from the ground up, spanning engineering, infrastructure, data, product, and domain-specific mortgage servicing expertise. This is a hands-on, full-cycle recruiting role with a strong emphasis on sourcing, requiring someone who can operate strategically while executing at a high level in a fast-paced, evolving environment. The ideal candidate brings deep experience recruiting for complex technical and product roles and has the ability to identify niche talent, engage passive candidates, and drive hiring outcomes aligned to business priorities. Experience supporting technology hiring within financial services, mortgage, or loan servicing environments—especially involving automation—is highly valued. What You’ll Support Hiring For - Engineering: Backend Engineers, Product Engineers, Design Engineers - Leadership: Lead Engineers across backend, product, infrastructure, and data - Infrastructure: Infrastructure Engineers and platform-focused roles - Data: Data Engineers, including domain-specific roles aligned to mortgage servicing - Product & Operations: Product-focused roles and a Product Operations / Chief of Staff-type function These roles will collectively support the buildout of a modern, scalable product ecosystem with strong ties to mortgage servicing and operational automation. Contract Details - Duration: 6-month contract with potential for extension - Location: Remote (U.S. or Toronto, Canada) - Compensation: Competitive hourly rate based on experience Responsibilities - Partner with hiring managers, product leaders, and technology stakeholders to define hiring needs and success profiles - Lead full-cycle recruiting, including intake, sourcing, screening, interview management, and offer negotiation - Design and execute targeted sourcing strategies to identify high-caliber, often passive, technical talent - Build and maintain high-quality pipelines, emphasizing candidate quality over volume - Engage candidates through multi-channel outreach, including LinkedIn, GitHub, and technical communities - Assess candidates for technical depth, problem-solving ability, and domain relevance - Provide market insights on talent availability, compensation trends, and hiring challenges - Manage multiple requisitions simultaneously while maintaining strong stakeholder communication - Deliver a strong, credible candidate experience in competitive markets - Track recruiting activity and ensure accountability across hiring workflows Qualifications - 4+ years of experience recruiting for technical and/or product roles - Proven success hiring for complex, hard-to-fill technical positions - Strong sourcing capabilities with a track record of engaging passive candidates - Ability to understand technical concepts and partner credibly with engineering and product leaders - Experience operating in fast-paced, project-driven environments - Strong communication, organization, and stakeholder management skills - Experience with ATS systems (e.g., Workday, iCIMS) and sourcing tools (LinkedIn, StackOverflow, Dice.com, Wellfound/BuiltIn, etc.) Preferred Experience - Experience hiring within financial services, mortgage, or loan servicing environments - Exposure to or hiring for mortgage servicing platforms, workflows, or automation initiatives - Experience supporting AI, data, or emerging technology teams - Background engaging with technical communities or niche talent ecosystems

Role Description The Chief of Staff, AI Special Projects is a high-agency operating role that reports to the Head of Engineering and helps a rapidly growing AI team operate with speed, clarity, and follow-through while building AI-enabled platforms inside a complex, high-stakes investment and financial services environment. This role is designed for a highly capable, technically curious operator who wants to work directly with Engineering leadership, learn quickly through close mentorship, and grow into broader ownership as the team scales. The expectation is not that this person has all the answers on day one; the expectation is that they bring strong judgment, learning velocity, organization, follow-through, and comfort operating in uncertainty. This role is a force multiplier for product development, Engineering leadership leverage, daily execution, and the operating rhythm required to scale quickly. Sitting at the epicenter of Engineering, Product, and domain Subject Matter Experts (SMEs), this person will help: - Organize priorities - Capture context - Run the operating cadence - Support platform health - Source critical talent - Unblock work Few roles offer this combination of access, urgency, mentorship, and learning curve: a front-row seat to technology, startup-style AI product building, and a cutting-edge financial services environment. You will see how ambiguous business problems become prototypes, evaluations, production launches, and scaled workflows, while learning directly from Engineering leadership and a founding AI team. This role will start with strong execution support, context capture, follow-through, and operating cadence, and is expected to grow into broader ownership of special projects, decision visibility, and cross-functional execution. This is a fully remote position that offers a competitive salary range of $120,000 to $180,000, plus an annual bonus. You'll also receive an excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors. Qualifications - Hunger to learn, high agency, excellent organization, and excellent written and verbal communication skills - Strong technical fluency and comfort using AI tools and platforms - Comfort operating in ambiguous environments - Exceptional learning velocity and comfort growing into broader responsibility quickly - Strong follow-through: remembering details, closing loops, keeping people accountable - Strong curiosity about AI, product development, engineering, platform operations, financial markets, and complex workflows - Strong judgment, discretion, and maturity in a regulated, high-stakes environment - Ability to work well with technical, product, business, operational, recruiting, and vendor stakeholders - Bias toward action and continuous improvement Requirements - Exposure to startups, consulting, operations, product, engineering, AI tools, automation, recruiting, team-building, or workflow improvement - Experience using AI tools for research, writing, analysis, coding, automation, project management, or workflow acceleration - Experience working with operators, domain experts, customers, executives, technical teams, candidates, or external partners - Experience organizing teams, programs, labs, communities, side projects, events, operational initiatives, or other complex workstreams Benefits - Competitive salary range of $120,000 to $180,000 - Annual bonus - Medical coverage starting on day one - Company-matched 401(k) Company Description Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence, and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.

Role Description The Lead Data Engineer on the Nebula team plays a significant technical leadership role in shaping and scaling the data foundation that powers analytics, reporting, AI development, and operational decision-making across the organization. This role combines hands-on data engineering execution with practical team leadership, helping the organization build reliable, flexible, and production-ready data systems. The Lead Data Engineer heads a lean, high-caliber squad of data engineers, while remaining deeply hands-on in the design, development, and operation of core data systems. The role balances direct technical contribution with mentoring, coaching, coordination, and day-to-day support for the engineers on the squad. Working across ingestion, transformation, storage, modeling, orchestration, and delivery, this role partners closely with Product, Engineering, AI, Analytics, and domain Subject Matter Experts (SMEs) to translate complex business processes into scalable data platforms, pipelines, and trusted datasets. This role owns the technical direction for core data capabilities, including ETL/ELT, batch and real-time processing, OLTP and OLAP systems, BI-ready data models, and cloud-based data infrastructure in a regulated, high-stakes environment. Success requires strong architectural judgment, operational discipline, and the ability to raise the technical bar for both systems and people. This is a fully remote position that offers a competitive salary range of $220,000 to $300,000, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors. Responsibilities - Strategic Technical Leadership - Own the architecture and evolution of core data systems, including ingestion, transformation, orchestration, storage, modeling, and delivery layers - Set technical direction for ETL/ELT, batch processing, real-time pipelines, OLTP and OLAP systems, and BI-ready data assets - Make pragmatic architecture decisions that balance scalability, reliability, security, performance, cost, and delivery speed - Establish engineering standards, reusable patterns, and design principles that improve quality and leverage across the data platform - Hands-On Data Engineering Delivery - Lead the design, build, rollout, and operations of greenfield data infrastructure - Build and maintain complex data pipelines across diverse source and destination systems, including databases, APIs, files, SaaS platforms, event streams, and internal applications - Design and optimize data models, warehouse schemas, semantic layers, and curated datasets for analytics, reporting, AI, and product use cases - Contribute directly to critical implementation work, including writing code, code and design reviews, migrations, reliability improvements, and production issue resolution - Squad Leadership & Management - Lead a lean, high-caliber squad of data engineers, spending focused time mentoring, coaching, managing, and coordinating the team - Develop engineers through regular feedback, technical guidance, code reviews, career support, and clear expectations around quality and ownership - Help prioritize team work, clarify scope, remove blockers, and ensure the squad delivers reliably against business and technical goals - Contribute to hiring, onboarding, performance development, and team operating rhythms as the data engineering function grows - Cloud Platform & Production Operations - Deploy, operate, and improve data pipelines, data stores, and supporting infrastructure on major cloud platforms such as AWS, GCP, or Azure - Drive strong practices for CI/CD, infrastructure-as-code, automated testing, monitoring, alerting, and incident response - Ensure data systems are observable, fault-tolerant, recoverable, and maintainable in production - Identify opportunities to reduce operational toil, improve platform reliability, and manage cloud infrastructure costs effectively - Data Quality, Governance & Trust - Define and enforce standards for data quality, validation, reconciliation, lineage, schema evolution, metadata, and documentation - Establish patterns for data contracts, ownership, SLAs, and runbooks that help downstream teams trust and use data confidently - Partner with security, compliance, and business stakeholders to support privacy, auditability, access controls, and regulated data handling - Raise the maturity of data governance and reliability practices without slowing down pragmatic delivery - Cross-Functional Partnership - Partner closely with Product, Engineering, AI, Analytics, and business stakeholders to align data architecture with organizational priorities - Translate ambiguous business needs and operational workflows into clear technical plans, milestones, and production-ready solutions - Serve as a senior technical point of contact for data-heavy initiatives, communicating tradeoffs, risks, sequencing, and timelines clearly - Enable downstream consumers, including analysts, product teams, data scientists, and operational users, through reliable and well-modeled data assets - Culture & Craft - Contribute to a culture of ownership, curiosity, operational rigor, pragmatism, and engineering excellence - Raise the bar for the team through thoughtful design, clear abstractions, strong reviews, and sound technical judgment - Balance staff-level technical depth with practical people leadership, helping the team grow while continuing to ship high-quality systems Qualifications - 5-8+ years of experience building and operating production-grade data pipelines, platforms, and distributed data systems - 2+ years of experience leading, mentoring, or managing data engineers in a tech lead, staff-level project lead, engineering manager, or TLM capacity - Strong hands-on experience with industry-standard tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI - Deep understanding of OLTP and OLAP systems, including the ability to design architectures that support transactional, analytical, and operational workloads - Experience building flexible data pipelines across many source and destination types, including databases, APIs, files, queues, event streams, SaaS platforms, and internal systems - Strong experience with both batch and real-time processing patterns, including tradeoffs in latency, reliability, cost, and operational complexity - Experience deploying and operating cloud-based data infrastructure on AWS, GCP, or Azure - Advanced SQL and data modeling expertise, including schema design, warehouse optimization, semantic modeling, and performance tuning - Strong programming ability in languages commonly used in data engineering, such as Python, Java, Scala, Go, or similar - Comfort with CI/CD, infrastructure-as-code, automated testing, observability, incident response, and production operations for data systems - Strong architectural judgment in ambiguous environments where systems must balance speed, reliability, compliance, maintainability, and long-term leverage - Clear communication skills with both technical and non-technical teammates, including the ability to explain tradeoffs and influence direction Preferred Experience - Experience operating as a Technical Lead or Tech Lead Manager responsible for both technical implementation, technical direction, and people development - Experience with modern orchestration and transformation tools such as Airflow, Dagster, dbt, or similar platforms - Experience with cloud-native warehouses or lakehouse platforms such as Snowflake, BigQuery, Redshift, Databricks, or equivalent technologies - Experience with streaming systems such as Kafka, Kinesis, Pub/Sub, Flink, Spark Streaming, or similar technologies - Experience enabling BI and self-service analytics through curated datasets, semantic layers, and reporting platforms such as Looker, Tableau, Power BI, or similar tools - Experience building data platforms that support AI, machine learning, decisioning, or LLM-powered workflows - Experience scaling a data engineering function, including technical standards, operating rhythms, hiring, onboarding, and team development - Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains A Note to Candidates You do not need prior fintech or finance experience to succeed in this role. If you are a senior data engineer with strong architectural judgment, a hands-on builder mindset, and the ability to develop other engineers, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply. Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law. #LI-Remote

Role Description The Data Engineer, Mortgage Servicing on the Nebula team acts as the mortgage servicing data subject matter expert and plays a critical role in building and evolving the data foundation that powers analytics, reporting, AI development, and operational decision-making across the organization. This role is responsible for designing, building, and maintaining reliable, scalable, and flexible data systems that support a wide range of internal and external use cases. - Requires domain awareness in mortgage and servicing-related data environments. - Understanding of the complexities associated with loan-level lifecycle data, transaction processing, cash movement, and reconciliation across systems. - Must be able to translate business workflows and system behavior into accurate, auditable data structures that support downstream reporting, operational processes, and regulatory requirements. - Contributes to the development and evolution of core data capabilities, including batch and real-time pipelines, operational and analytical data stores, semantic models, and BI-ready datasets. - Expected to operate effectively in a modern engineering environment, using automation, observability, and infrastructure-as-code practices. - Help enable downstream analytics, reporting, product capabilities, and AI systems by ensuring that data is trustworthy, accessible, and fit for purpose. Responsibilities - Data Pipeline Development: - Design, build, and maintain robust data pipelines for a wide variety of input and output sources, including internal systems, third-party platforms, files, APIs, event streams, and databases. - Develop scalable ETL and ELT workflows for both batch and real-time processing. - Ensure pipelines are reliable, testable, observable, and easy to extend as business needs evolve. - Build reusable data integration patterns that support growing volumes, new source systems, and downstream consumers across analytics, applications, and AI initiatives. - Data Platform & Storage: - Design and manage data architectures that support OLTP, OLAP, and reporting workloads across operational and analytical environments. - Build and optimize data models, warehouse schemas, and curated datasets for analytics and BI use cases. - Contribute to the design and operation of modern data platforms, including warehouses, lakehouses, streaming systems, and supporting orchestration frameworks. - Help define patterns for data storage, partitioning, performance optimization, retention, and lifecycle management. - Servicing-Oriented Data Modeling & Integrity: - Design and maintain data models that accurately reflect loan-level lifecycle events, including payment activity, balances, adjustments, and status changes. - Ensure consistency and reconciliation across systems where transactional, financial, and reporting data must align. - Identify and resolve discrepancies across source systems, and build data structures that support accurate, auditable outputs for downstream operational processes, reporting, and decisioning. - Cloud Deployment & Operations: - Deploy, operate, and improve data pipelines and data stores on major cloud platforms such as AWS, GCP, or Azure. - Use infrastructure-as-code, CI/CD, and automation practices to improve deployment speed, consistency, and reliability. - Monitor production data systems using logging, alerting, and observability tooling to proactively identify and resolve issues. - Support secure, resilient, and cost-conscious operation of cloud-based data infrastructure. - Data Quality, Reliability & Governance: - Implement data quality checks, validation rules, reconciliation processes, and monitoring to ensure trustworthy data across systems. - Establish and maintain standards for lineage, documentation, metadata, schema evolution, and operational runbooks. - Partner with stakeholders to improve data accessibility, consistency, and usability while maintaining appropriate controls and governance. - Contribute to practices that support security, privacy, auditability, and compliance in a regulated environment. - Cross-Functional Collaboration: - Partner closely with Product, Engineering, and business stakeholders to understand data needs, workflows, and constraints. - Translate business and operational requirements into clean, scalable, and maintainable data solutions. - Support downstream consumers of data, including analysts, researchers, product teams, and operational users. - Communicate clearly with both technical and non-technical stakeholders about data availability, quality, tradeoffs, and delivery timelines. - Iteration & Continuous Improvement: - Continuously improve pipeline performance, reliability, scalability, and developer productivity. - Identify opportunities to simplify architecture, reduce operational toil, and improve data platform leverage across teams. - Operate with a strong bias toward action and iterative delivery, moving quickly from problem definition to implementation and improvement. - Help raise the bar on engineering quality through thoughtful design, testing, documentation, and operational discipline. Qualifications - 5-8+ years of experience building and operating production-grade data pipelines and data systems. - Prior experience in mortgage, servicing, or similarly regulated financial domains. - Strong experience with industry-standard tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI. - Experience working with both OLTP and OLAP systems, with a strong understanding of the tradeoffs between transactional and analytical workloads. - Experience building flexible data pipelines that integrate with many different source and destination types, including databases, APIs, files, message queues, SaaS platforms, and event streams. - Experience supporting both batch and real-time data processing patterns. - Experience deploying and operating data infrastructure on major cloud platforms such as AWS, GCP, or Azure. - Strong SQL skills and experience with data modeling, transformation frameworks, and performance optimization. - Experience building AI-powered capabilities on top of LLMs, including orchestration, evaluation, and data integration patterns. - Experience with modern programming languages commonly used in data engineering, such as Python, Java, Scala, or Go. - Comfort working with CI/CD, infrastructure-as-code, observability, and production operations for data systems. - Strong judgment in ambiguous environments where requirements evolve and systems must balance speed, reliability, and flexibility. - Clear communication skills with both technical and non-technical teammates. Preferred Experience - Experience with modern orchestration and transformation tools such as Airflow, Dagster, dbt, or similar platforms. - Experience with cloud-native data warehouses or lakehouse platforms such as Snowflake, BigQuery, Redshift, Databricks, or equivalent technologies. - Experience with streaming and real-time data platforms such as Kafka, Kinesis, SQS, or similar systems. - Experience enabling BI and self-service analytics through curated datasets, semantic layers, and reporting platforms such as Looker, Power BI, Tableau, or similar tools. - Experience working with loan-level or transaction-heavy financial data within residential mortgage servicing domains. - Experience dealing with data reconciliation challenges across multiple systems, particularly where cash balances, or investor/reporting outputs must align. - Experience building data platforms that support AI, machine learning, or decisioning workflows. - Experience improving data quality, reliability, cost efficiency, and platform scalability as a system grows. A Note to Candidates If you are a strong data engineer with solid technical judgment, a systems mindset, and excitement for solving complex data problems, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply. Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law. #LI-Remote

Role Description The Data Engineer on the Nebula team plays a critical role in building and evolving the data foundation that powers analytics, reporting, AI development, and operational decision-making across the organization. This role is responsible for designing, building, and maintaining reliable, scalable, and flexible data systems that support a wide range of internal and external use cases. - Working across data ingestion, transformation, storage, modeling, and delivery. - Partnering closely with Product, Engineering, AI, Analytics, and domain Subject Matter Experts (SMEs). - Translating complex business processes and data needs into production-ready data pipelines and platforms. - Contributing to the development and evolution of core data capabilities, including batch and real-time pipelines, operational and analytical data stores, semantic models, and BI-ready datasets. - Operating effectively in a modern engineering environment using automation, observability, and infrastructure-as-code practices. - Ensuring that data is trustworthy, accessible, and fit for purpose. Responsibilities - Data Pipeline Development: - Design, build, and maintain robust data pipelines for a wide variety of input and output sources. - Develop scalable ETL and ELT workflows for both batch and real-time processing. - Ensure pipelines are reliable, testable, observable, and easy to extend as business needs evolve. - Build reusable data integration patterns that support growing volumes, new source systems, and downstream consumers. - Data Platform & Storage: - Design and manage data architectures that support OLTP, OLAP, and reporting workloads. - Build and optimize data models, warehouse schemas, and curated datasets for analytics and BI use cases. - Contribute to the design and operation of modern data platforms. - Help define patterns for data storage, partitioning, performance optimization, retention, and lifecycle management. - Cloud Deployment & Operations: - Deploy, operate, and improve data pipelines and data stores on major cloud platforms. - Use infrastructure-as-code, CI/CD, and automation practices to improve deployment speed, consistency, and reliability. - Monitor production data systems using logging, alerting, and observability tooling. - Support secure, resilient, and cost-conscious operation of cloud-based data infrastructure. - Data Quality, Reliability & Governance: - Implement data quality checks, validation rules, reconciliation processes, and monitoring. - Establish and maintain standards for lineage, documentation, metadata, schema evolution, and operational runbooks. - Partner with stakeholders to improve data accessibility, consistency, and usability. - Contribute to practices that support security, privacy, auditability, and compliance. - Cross-Functional Collaboration: - Partner closely with Product, Engineering, and business stakeholders to understand data needs. - Translate business and operational requirements into clean, scalable, and maintainable data solutions. - Support downstream consumers of data, including analysts, researchers, product teams, and operational users. - Communicate clearly with both technical and non-technical stakeholders about data availability, quality, tradeoffs, and delivery timelines. - Iteration & Continuous Improvement: - Continuously improve pipeline performance, reliability, scalability, and developer productivity. - Identify opportunities to simplify architecture, reduce operational toil, and improve data platform leverage. - Operate with a strong bias toward action and iterative delivery. - Help raise the bar on engineering quality through thoughtful design, testing, documentation, and operational discipline. Qualifications - 2-4+ years of experience building and operating production-grade data pipelines and data systems. - Strong experience with industry-standard tools and platforms for ETL/ELT, orchestration, data warehousing, streaming, and BI. - Experience working with both OLTP and OLAP systems. - Experience building flexible data pipelines that integrate with many different source and destination types. - Experience supporting both batch and real-time data processing patterns. - Experience deploying and operating data infrastructure on major cloud platforms. - Strong SQL skills and experience with data modeling, transformation frameworks, and performance optimization. - Experience with modern programming languages commonly used in data engineering. - Comfort working with CI/CD, infrastructure-as-code, observability, and production operations for data systems. - Clear communication skills with both technical and non-technical teammates. Preferred Experience - Experience with modern orchestration and transformation tools. - Experience with cloud-native data warehouses or lakehouse platforms. - Experience with streaming and real-time data platforms. - Experience enabling BI and self-service analytics through curated datasets. - Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains. - Experience building data platforms that support AI, machine learning, or decisioning workflows. Benefits - Competitive salary range of $220,000 to $300,000, plus an annual bonus. - Medical coverage starting on day one. - Company-matched 401(k). A note to candidates You do not need prior fintech or finance experience to succeed in this role. If you are a strong data engineer with solid technical judgment, a systems mindset, and excitement for solving complex data problems, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply. Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.

Role Description The Product Engineer on the Horizon team plays a critical role in advancing platform capabilities through a combination of building new, next-generation solutions and evolving existing technology. This role is responsible for translating complex operational workflows into intuitive, reliable, and production-ready software. - Working across the stack, this individual partners closely with Product, Engineering, and domain Subject Matter Experts (SMEs) to gain a deep understanding of user needs. - Rapidly turns that understanding into high-quality product experiences that feel innovative, natural, and trustworthy. - Contributes to the development and evolution of core systems, spanning net-new capabilities and enhancements to existing technology across frontend, backend, data, and cloud infrastructure within a regulated, high-stakes environment. - Ensures that what is delivered is not only technically sound but also aligned with business intent, operational realities, and user expectations. - Raises the bar for product quality, system reliability, and velocity as the platform continues to evolve. Qualifications - 2-4+ years of experience building and shipping high-quality, production software. - Strong experience with a modern frontend stack, including TypeScript, React, and/or Next.js, styling systems/libraries, and modern build tooling. - Strong product instincts, great design taste, and a clear sense for building products that feel natural and intuitive to end users. - Experience with rapid prototyping and tools/workflows that enable fast iteration cycles. - Experience building modern backend systems using Python, Go, Rust, or similar languages, including APIs, middleware, ORMs, authentication, authorization, and security-minded application design. - Experience building and shipping software on major cloud platforms such as AWS, GCP, or Azure. - Experience working in a modern software development environment and shipping quickly, with high degrees of ownership. - Comfort navigating and iteratively improving on shared CI/CD, Observability, Reporting, Analytics, and Data-heavy Systems. - Good judgment in ambiguous environments where the problem is not fully defined yet. - The ability to communicate clearly with both technical and non-technical teammates. - A bias toward action: thrives in an environment where learning quickly, shipping thoughtfully, and improving through iteration is essential. Requirements - Experience building workflow-heavy products, internal tools, or systems for operational teams. - Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains. - Experience working closely with operators, domain experts, or customers. - Experience improving product quality, performance, reliability, or developer velocity as a system grows. - Experience working across the stack, from polished UI to backend services to production operations. Benefits - Competitive salary range of $140,000 to $180,000, plus an annual bonus. - Excellent benefits package, which includes medical coverage starting on day one. - Company-matched 401(k). Company Description Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence, and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.

Role Description The Design Engineer on the Horizon team plays a critical role in shaping the look, feel, and usability of the AI platform, from zero to one. This role turns product ideas, complex workflows, and user needs into polished interfaces that feel intuitive, trustworthy, and delightful across desktop and mobile experiences. Working across product design, frontend engineering, and AI-native workflows, this individual partners closely with Engineering, Product, Data, Security, Operations, and domain Subject Matter Experts (SMEs) to make sophisticated platform capabilities simple and useful for real users. This role contributes to the development and evolution of core product experiences, spanning: - Interaction design - Visual systems - Information architecture - Design systems - Responsive interfaces - Prototyping - Production frontend implementation - Accessibility - Performance - Usability within a regulated, high-stakes environment Success requires exceptional product taste, strong frontend craft, pragmatic systems thinking, and a bias toward shipping. The Design Engineer is expected to operate in an AI-native product environment, using modern design tools, coding agents, rapid prototyping workflows, and frontend frameworks to move quickly from concept to production. This is a fully remote position that offers a competitive salary range of $140,000 to $180,000, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors. Qualifications - 4-7+ years of experience designing and building high-quality software products, ideally in a fast-moving product engineering environment - Strong portfolio or body of shipped work demonstrating product taste, interaction design judgment, visual craft, and frontend implementation quality - Hands-on experience with Figma or similar design tools and a strong command of UX flows, hierarchy, typography, spacing, and visual polish - Strong frontend engineering experience with React, TypeScript, modern CSS, responsive layouts, component architecture, browser fundamentals, and production frontend practices - Experience turning rough ideas into working prototypes and then hardening successful prototypes into maintainable product experiences - Ability to design for desktop and mobile experiences, including responsive behavior, accessibility, performance, and cross-browser quality - Comfort working with AI-enabled, data-heavy, integration-heavy, or operationally critical product experiences where clarity and trust matter - Working knowledge of design systems, reusable components, interaction patterns, and frontend quality practices - Comfort using AI-native tools, coding agents, and rapid prototyping workflows to accelerate exploration and implementation - Good judgment in ambiguous environments where the path is not fully defined and the team needs to go from zero to one - Clear communication skills with both technical and non-technical teammates Requirements - Experience building design systems, internal platforms, developer tools, workflow products, or complex B2B software for fast-moving product teams - Experience in fintech, mortgage, lending, payments, insurance, or other regulated domains - Experience designing and building AI product experiences, including copilots, agentic workflows, human-in-the-loop review, trust surfaces, or model-output interfaces - Experience improving user activation, usability, frontend performance, accessibility, design consistency, or design-to-code velocity as systems grow A note to candidates You do not need prior fintech or finance experience to succeed in this role. If you are a design-minded builder with exceptional product taste, frontend craft, and excitement for learning a complex domain, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply. Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law. #LI-Remote

Role Description The Backend Engineer on the AI Platform team plays a critical role in building and evolving the backend systems that power internal products, customer-facing capabilities, AI-enabled workflows, and operational decision-making across the organization. This role is responsible for designing, building, testing, and operating reliable, scalable, and flexible services that support a wide range of internal and external use cases. This role contributes to the development and evolution of core backend and distributed systems capabilities, including: - Service-oriented architectures - APIs - Workflow orchestration - Event-driven integrations - Identity and permissions - Operational tooling - System interfaces Success requires strong technical depth, sound systems thinking, and the ability to build dependable solutions in a cloud-based, regulated, high-stakes environment. The Backend Engineer is expected to operate effectively in a modern engineering environment, using automation, observability, CI/CD, testing, and infrastructure-as-code practices to deploy, manage, and improve production services. This is a fully remote position that offers a competitive salary range of $140,000 to $240,000, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors. Qualifications - 3-5+ years of experience building and operating production-grade backend systems, APIs, services, or distributed applications - Strong software engineering fundamentals, including data structures, algorithms, system design, debugging, testing, and code quality - Experience designing, building, maintaining, and debugging services that run in production and support real users or business-critical workflows - Experience with modern backend programming languages such as Python, Go, C++, Rust, Java, Kotlin, Scala, TypeScript, or C# - Experience with API design, service boundaries, event-driven or asynchronous architectures, relational data stores, and non-relational data stores - Experience building transactional systems where correctness, idempotency, consistency, reconciliation, and auditability matter - Experience deploying and operating backend services on major cloud platforms such as AWS, GCP, or Azure - Strong SQL skills and comfort with application data modeling, schema evolution, migrations, query performance, and data access patterns - Experience building AI-powered capabilities on top of LLMs, including orchestration, retrieval, evaluation, tool integrations, and workflow automation - Comfort working with CI/CD, infrastructure-as-code, observability, incident response, and production operations for backend systems - Strong judgment in ambiguous environments where requirements evolve and systems must balance speed, reliability, security, and flexibility - Clear communication skills with both technical and non-technical teammates Requirements - Design, build, and maintain production backend services for a wide variety of internal and external use cases, including product workflows, operational tools, integrations, APIs, and AI-enabled applications - Develop well-structured APIs, domain models, service interfaces, and business logic that are easy to understand, test, operate, and extend - Build scalable backend workflows that support complex business processes across loans, documents, accounts, users, permissions, vendors, and operational decision making - Ensure backend services are reliable, testable, observable, and resilient as business needs, data volumes, and product surfaces evolve - Contribute to service architectures that support transactional, operational, analytical, and AI-driven workloads across production environments - Integrate with internal systems, third-party platforms, vendor APIs, databases, files, message queues, event streams, and cloud services - Design patterns for service boundaries, idempotency, consistency, retries, failure handling, schema evolution, versioning, and backward compatibility - Help define practical architecture standards that balance speed, simplicity, reliability, security, and long-term maintainability - Deploy, operate, and improve backend services on major cloud platforms such as AWS, GCP, or Azure - Use infrastructure-as-code, CI/CD, automated testing, and deployment automation to improve release speed, consistency, and reliability - Monitor production services using logging, tracing, metrics, alerting, and observability tools to proactively identify and resolve issues - Support secure, resilient, and cost-conscious operation of cloud-based backend infrastructure and application services - Build systems with strong operational discipline, including attention to latency, availability, scalability, correctness, incident response, and production support - Implement authentication, authorization, permissions, audit logging, data protection, and secure service-to-service communication patterns - Establish and maintain standards for API documentation, service ownership, runbooks, operational metrics, change management, and production readiness - Contribute to practices that support security, privacy, auditability, compliance, and risk management in a regulated environment - Partner closely with Product, Engineering, Data, AI, Design, Operations, and business stakeholders to understand workflows, user needs, constraints, and delivery priorities - Translate business and operational requirements into clean, scalable, maintainable, and secure backend solutions - Support downstream consumers of backend capabilities, including product teams, analysts, researchers, AI systems, operational users, and external integrations - Communicate clearly with both technical and non-technical stakeholders about system behavior, tradeoffs, risks, dependencies, and delivery timelines - Continuously improve service performance, reliability, scalability, security, and developer productivity - Identify opportunities to simplify architecture, reduce operational toil, improve shared platform leverage, and make systems easier to reason about - Operate with a strong bias toward action and iterative delivery, moving quickly from problem definition to implementation, validation, and improvement - Help raise the bar on engineering quality through thoughtful design, code review, testing, documentation, mentorship, and operational discipline Benefits - Competitive salary range of $140,000 to $240,000 - Annual bonus - Medical coverage starting on day one - Company-matched 401(k) Company Description Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.

Role Description The Lead Backend Engineer on the AI Platform team plays a critical role in building, evolving, and leading the backend systems and engineering practices that power internal products, customer-facing capabilities, AI-enabled workflows, and operational decision-making across the organization. This role combines hands-on backend engineering depth with technical leadership, delivery ownership, and mentorship for engineers working on business-critical systems. This role contributes to the development and evolution of core backend capabilities, including: - Service-oriented architecture - APIs - Workflow orchestration - Event-driven integrations - Identity and permissions - Operational tooling In addition, the Lead Backend Engineer will drive buildouts of: - AI application infrastructure - LLM-powered product capabilities - Agentic workflows - Retrieval-augmented systems - Evaluation pipelines - Shared platform patterns Success requires strong technical judgment, sound systems thinking, and the ability to guide a team toward simple, scalable, and maintainable solutions in a cloud-based, regulated, high-stakes environment. The Lead Backend Engineer is expected to operate effectively in a modern engineering environment, using: - Automation - Observability - CI/CD - Testing - Infrastructure-as-code - AI-assisted development practices This is a fully remote position that offers a competitive salary range of $220,000 to $300,000, plus an annual bonus. You'll also receive our excellent benefits package, which includes medical coverage starting on day one and a company-matched 401(k). Compensation may vary based on experience, location, and other job-related factors. Qualifications - 5-8+ years of experience building and operating production-grade backend systems, APIs, services, or distributed applications - 2+ years of experience operating in a technical lead, team lead, staff-level project lead, engineering manager, or equivalent engineering leadership capacity - Strong software engineering fundamentals, including data structures, algorithms, system design, debugging, testing, code quality, and pragmatic architecture decision-making - Experience designing, building, maintaining, and debugging services that run in production and support real users or business-critical workflows - Experience with modern backend programming languages such as Python, Go, C++, Rust, Java, Kotlin, Scala, TypeScript, or C# - Experience with API design, service boundaries, event-driven or asynchronous architectures, relational data stores, and non-relational data stores - Experience building transactional systems where correctness, idempotency, consistency, reconciliation, and auditability matter - Experience deploying and operating backend services on major cloud platforms such as AWS, GCP, or Azure - Experience building AI-enabled product capabilities on top of LLMs, foundation models, retrieval systems, embedding and search infrastructure, agent or tool-calling patterns, workflow orchestration, structured outputs, and human-in-the-loop review - Experience integrating AI capabilities with backend systems, permissions, audit trails, document workflows, data pipelines, APIs, operational decisioning, and business-critical user experiences - Demonstrated ability to use AI-assisted development tools to improve engineering velocity while maintaining code quality, security, review discipline, and accountability for technical decisions - Strong SQL skills and comfort with application data modeling, schema evolution, migrations, query performance, and data access patterns - Experience leading technical design, breaking down ambiguous problems, sequencing work, managing dependencies, and helping engineers make high-quality implementation decisions - Experience mentoring engineers through design review, code review, debugging, production support, career development, and feedback - Strong judgment in ambiguous environments where requirements evolve and systems must balance speed, reliability, security, compliance, and flexibility Requirements - Experience in fintech, mortgage, lending, payments, insurance, banking, capital markets, or other regulated domains - Experience with queues, streaming, and event-driven platforms such as Kafka, Kinesis, SQS/SNS, Pub/Sub, RabbitMQ, or similar systems - Experience building secure identity, access control, permissions, audit trail, policy, or compliance-oriented backend capabilities - Experience building high-volume, low-latency, multi-tenant, B2B, enterprise, or internal platform systems - Experience with AI platform components such as model APIs, prompt management, embeddings, vector databases, retrieval pipelines, function calling, model routing, evaluation harnesses, and AI observability tooling - Experience improving system reliability, cost efficiency, developer productivity, team execution, and operational scalability as a platform grows Benefits - Medical coverage starting on day one - Company-matched 401(k) - Annual bonus A Note to Candidates You do not need prior fintech or finance experience to succeed in this role. If you are a strong backend engineering lead with solid technical judgment, a product mindset, and excitement for leading engineers through complex backend and AI-enabled systems problems, we would love to hear from you. If your background does not line up perfectly with every bullet, but this role feels like the kind of work you want to do, please apply. Bayview is an Equal Employment Opportunity employer. All aspects of consideration for employment and employment with the Company are governed on the basis of merit, competence and qualifications without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other category protected by federal, state, or local law.