Role Description - Phase 1 build of the AI orchestrator — intent & slot extraction, policy engine, planner, composer LLM, output guardrails, PII redaction. - Basic RAG for motor policy Q&A. - Authenticated claim-status lookup. - Prompt engineering. Active June–July 2026 (~2 months; duration rounded up to nearest 3-month option). An AI engineer who has shipped LLM-based assistants with RAG and tool-calling into production, strong on prompt engineering and grounding/guardrails. Qualifications - LLM / GenAI application development - Retrieval-augmented generation (RAG) - Prompt engineering - API / tool integration - Python (assumed — confirm) Requirements - OCI Generative AI - Arabic NLP - Insurance / regulated domain - Guardrails & PII handling

Role Description We are seeking an experienced AI Engineer focused on Agentic AI and Workflow Automation to architect, build, and deploy intelligent systems that could transform our business. This role will be responsible for designing and implementing AI agents, autonomous workflows, and enterprise automation systems that drive operational efficiency, reduce cycle times, improve borrower and broker experience, enhance compliance, and increase EBITDA through scalable automation. The ideal candidate combines expertise in LLMs, agentic architectures, orchestration frameworks, and workflow automation with a practical understanding of enterprise systems integration and regulated financial services environments. Essential Duties and Responsibilities - Agentic AI Architecture & Development - Design, develop, and deploy AI agents and multi-agent systems to automate mortgage workflows across the loan lifecycle. - Build intelligent orchestration frameworks capable of autonomous decision support, task execution, and workflow routing. - Develop AI copilots and internal assistants for underwriting, loan processing, sales, operations, secondary markets, compliance, capital markets, and executive leadership. - Create AI-powered exception handling and escalation frameworks for complex loan scenarios. - Workflow Automation - Identify, redesign, and automate high-friction operational workflows across the mortgage platform. - Develop automation solutions for loan intake, document classification, income and asset analysis, credit review, conditions management, broker communication, borrower engagement, QC and compliance reviews, and post-close processes. - LLM & AI Engineering - Implement Retrieval-Augmented Generation (RAG) systems using lending guidelines, overlays, investor matrices, and SOPs. - Build prompt orchestration, memory systems, and agent reasoning frameworks. - Evaluate and deploy emerging AI technologies for document intelligence, NLP, computer vision, and decision support. - Systems Integration - Integrate AI systems with LOS platforms, CRM systems, pricing engines, OCR/document recognition tools and data platforms. - Develop APIs and middleware to enable seamless AI workflow orchestration. - Governance, Risk & Compliance - Ensure AI implementations align with mortgage regulatory requirements and governance standards. - Design controls around explainability, auditability, model monitoring, and human-in-the-loop approvals. - Strategy & Innovation - Help define and execute the enterprise AI strategy. - Prioritize high-ROI automation opportunities that improve revenue, pull-through, turn times, cost-to-originate, scalability, and EBITDA. Qualifications - 5+ years of software engineering, AI engineering, or machine learning experience. - 2+ years building LLM-based applications or agentic AI systems. - Experience with orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or MCP-based architectures. - Strong Python development skills and experience with APIs, vector databases, prompt engineering, RAG architectures, and workflow automation. Preferred Qualifications - Experience in mortgage lending, fintech, banking, or financial services. - Familiarity with Non-QM underwriting guidelines including DSCR, Bank Statement, Asset Qualifier, ITIN, Foreign National, and Jumbo products. - Experience with mortgage LOS platforms and deploying AI in regulated environments. Technical Stack (Preferred) - Languages: Python, SQL, JavaScript/TypeScript - AI/LLM: OpenAI, Anthropic, open-source LLMs, Hugging Face - Automation: n8n, UiPath, Zapier, Make, Apache Airflow - Cloud & DevOps: AWS, Azure, GCP, Docker, Kubernetes, CI/CD Benefits - Medical, dental, vision, wellness programs, EAP counseling services, FSA & HSA. - Company sponsored life insurance for employee, voluntary life insurance for employee, spouse and child. - AD&D Insurance, voluntary short-term and long-term disability, critical illness insurance, accident insurance. - Legal assistance, pet insurance, living will and trust preparation discounts, commuter program. - Annual walking challenge, employee appreciation events and monthly sales awards.

Role Description We are hiring a hands-on Principal Engineer to lead our new AI-first engineering pod — a small, high-trust team that ships real product and platform work in our existing payments codebase, then helps the rest of engineering adopt what works. This is not an advisory architecture role. You will code, review, unblock, and ship — while building the AI-first operating model from evidence, not slides. Framework work should emerge from what the pod proves in production: tooling choices, review practices, guardrails, and team habits that other squads can pick up without reinventing the wheel. Over time, as the model proves itself, the pod is expected to grow into a full scrum team and potentially split into two scrum teams, as delivery capacity and adoption mature. You should be comfortable starting lean and hands-on, then evolving into a team lead who can run backlog, ceremonies, and engineering practices at squad scale. AI-first means agent-first development with human checkpoints where they matter— orchestrated pipelines, not a developer alone in a chat window. Work flows through defined steps: intake → context assembly → agent execution → automated review gates → human approval → production. Using Cursor or Copilot well is a baseline. We want someone who has designed and built agentic orchestration: pipelines that connect real systems (Slack, issue trackers, Git, CI/CD) and run multi-step agent workflows with guardrails, audit trails, and human escalation at the right points. It does not mean unmanned codegen or bypassing regulated change control. Key Responsibilities - Lead pod delivery end-to-end: backlog refinement, technical breakdown, implementation, review, and release. - Design and build agentic orchestration pipelines — e.g. a bug reported in Slack or Plane flowing through triage, context gathering, fix attempt, PR creation, and automated review before a human merges. - Wire agentic review triggers into PR and CI/CD workflows: security analysis, bug-risk review, test gap detection, dependency checks — with clear pass/fail/escalate behaviour and auditability. - Use AI-assisted development responsibly across coding, testing, debugging, refactoring, documentation, and code review — coaching the pod without bypassing engineering fundamentals. - Ship production-visible outcomes early and codify what works into standards, guardrails, and tooling choices the wider org can adopt. - Provide pragmatic technical leadership on pod-owned work and high-risk cross-cutting decisions; advise (not own) wider platform architecture. - Lead one high-leverage modernisation path the pod can execute — including assessment of our .NET Core 2.1 estate and a pragmatic upgrade recommendation. - Improve the pod’s path to production: Git workflows, CI/CD (Jenkins and/or GitHub Actions), testing expectations, and quality gates — then propose rollouts others can follow. - Grow the pod: hiring, onboarding, scrum maturity, and mentorship across distributed and offshore engineers. - Ensure everything ships with fintech-grade security, compliance, auditability, and operational discipline — including careful evaluation of AI vendor and tooling risk. Qualifications - 8+ years in software engineering, with senior technical leadership experience. - Strong hands-on skills in existing production codebases — not only greenfield. - Experience leading or contributing materially to a small team shipping real work. - Track record of mentoring and rolling out new engineering practices beyond your own team. - Practical, safe use of AI-assisted development tools. - Built agentic pipelines, not only used an AI IDE. - React/TypeScript and .NET/C# experience; strong architecture and communication skills. - Fintech, payments, or regulated environments. - Legacy .NET Core upgrades; Java or Go in production. - Growing a pod or small team into a stable scrum team (or leading multiple squads). - Creating engineering standards, test automation, or secure SDLC practices. - Using AI to accelerate codebase comprehension, refactoring, test generation, or migration planning. - Agentic SDLC automation: PR review agents, security scanning in CI/CD, bug-triage-to-fix pipelines, Slack or issue-tracker integrations. Benefits - Flexibility in work hours and location, with a focus on managing energy rather than time. - Access to online learning platforms and a budget for professional development. - A collaborative, no-silos environment, encouraging learning and growth across teams. - A dynamic social culture with team lunches, social events, and opportunities for creative input. - Health insurance. - Leave Benefits. - Provident Fund. - Gratuity.

Title: Senior AI Engineer – Developer Products Location: San Francisco, California Job Description: Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: - Business Insider named us an “enterprise startup to bet your career on” - Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world - Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America - Quartz ranked us the #1 best company for remote workers Senior AI Engineer – Developer Products Location: San Francisco, CA (Onsite/Hybrid) About the Role We are seeking an exceptional Senior Software Engineer to join our San Francisco team and build new developer products. In this role, you will design, build, and optimize AI-first experiences that empower developers to experiment, prototype, and integrate with our platform. You will collaborate closely with product, engineering, and developer relations teams to deliver robust, scalable, and intuitive services. This role requires a high technical bar, plus an emphasis on developer ergonomics, so we can deliver a delightful developer experience. Responsibilities - Design, build, and enhance AI services and APIs powering our developer sandbox, leveraging LLMs and custom ML models. - Develop well-architected, testable, and efficient Python code to support rapid prototyping and experimentation. - Implement and improve validation, monitoring, and observability for ML services within the sandbox environment. - Drive the full development lifecycle: from ideation and architecture to deployment and continuous improvement. - Collaborate with cross-functional teams to design developer-centric solutions and intuitive user experiences. - Continuously evaluate and optimize existing implementations for performance, scalability, and developer usability. - Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment. - Conduct code reviews and mentor team members to uphold high engineering standards. Requirements Qualifications / Experience / Technical Skills - Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience. - 5+ years of experience as an ML Engineer, Data Scientist, or similar role. - Strong Python programming skills and hands-on experience with NLP and LLM models. - Proven track record of deploying and maintaining ML services in production environments. - Solid understanding of network protocols, API design, and developer tooling. - Experience with relational and non-relational databases. - LLMops/MLops experience is a strong plus, especially in developer-facing products. - Experience building or supporting developer platforms, APIs, or sandbox environments is highly desirable. Soft Skills / Personal Characteristics - Collaborative team player with a passion for empowering developers and improving developer experience. - Adaptable, proactive, and creative—comfortable working in a dynamic, startup-like environment. - Strong problem-solving skills and a continuous improvement mindset. Join us in San Francisco and help shape the future of developer innovation with AI-powered sandbox experiences! The salary range for this role is dependent on experience and ranges from $170,000 to $250,000. We also provide stock options to all employees and generous benefits.