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• Diagnose business problems before building solutions • Own AI initiatives end-to-end, from stakeholder discovery and technical design through implementation, deployment, and iteration • Design, develop, and ship AI-powered solutions quickly • Improve organizational flow by building solutions that reduce bottlenecks • Integrate AI capabilities into existing systems and workflows • Partner closely with stakeholders across functions • Define and track success through business metrics and feedback loops
QuinStreet offers a decentralized online marketplace that empowers consumers by matching them with brands that meet their needs. A leader among “research and compare” networks,
Role Description We are looking for a Senior AI Developer & Cloud Architect to design, build, and own the AI-powered compliance scraping engine and cloud infrastructure layer for an internal platform monitoring up to 70,000 credit card offer pages per month. This is a hands-on, sole-builder contractor role that sits at the intersection of cloud architecture, AI engineering, and large-scale web scraping, with a clear mandate: deliver a production-grade system that detects compliance violations across issuer offer pages with high accuracy and controlled token costs. You will do this by: - Architecting the AWS environment from the ground up. - Building a containerized worker fleet that integrates Playwright rendering with Claude-powered contextual analysis. - Defining clean API contracts with the internal team that owns the Laravel control panel. This is not a managed-PaaS or prototype role. You will be accountable for end-to-end delivery — architecture, build, documentation, and knowledge transfer — owning the full scraping and AI pipeline from URL intake through compliance findings, screenshot evidence, and results delivery back to the portal. Responsibilities - Design and configure the production AWS environment (ECS/Fargate, SQS, API Gateway, RDS PostgreSQL, S3, IAM, CloudWatch) using infrastructure as code (Terraform or CDK). - Build a stateless, containerized worker fleet that integrates Playwright-based page rendering, structured rule evaluation, and Claude API analysis. - Implement token optimization strategies across the LLM pipeline — prompt engineering, context pruning, caching, model selection, and batching — with measurable cost outcomes. - Define and document API contracts, job payload schemas, and database write patterns with the internal Laravel portal team to enable parallel development. - Build third-party API ingestion and field-level diff-detection logic that automatically adjusts monitoring rules when product data changes. - Handle modern web rendering challenges at scale: JavaScript-heavy SPAs, interstitials, cookie consent overlays, dynamic content, viewport switching, and full-page screenshot capture. - Evaluate when LLM analysis is the correct tool versus a classifier or rules-based approach, and design the two-stage rule-engine-plus-AI pipeline accordingly. - Build and maintain a unit test suite covering all modules and APIs to ensure uptime and proper functionality. - Document every architecture decision, configuration, API contract, and operational procedure continuously — not as a final-week deliverable. - Deliver a complete runbook and knowledge transfer to the internal team at engagement close. - Operate independently end-to-end while coordinating closely with the internal portal team and reporting directly to the Senior Director, surfacing risks and trade-offs early. Requirements - Production backend Python experience, including async patterns, type hints, packaging, and testing. - Direct production experience designing and configuring AWS ECS/Fargate, SQS, API Gateway, RDS (PostgreSQL), S3, IAM, and CloudWatch, with infrastructure as code (Terraform or CDK). - Real shipped systems calling the Anthropic Claude API in production, with demonstrated experience in prompt design, structured output, error handling, and cost trade-offs. - Demonstrated track record reducing token spend on production LLM workloads, with specific before/after results you can walk through. - Working knowledge of other LLM providers sufficient to recommend cheaper or better alternatives for specific tasks. - Production Playwright experience at scale, including headless Chromium failure modes, network idle detection, dynamic content handling, viewport switching, and screenshot strategy. Selenium or Puppeteer experience does not substitute. - Machine learning fundamentals sufficient to evaluate when LLM analysis is the right tool versus a classifier or rules-based approach, and to reason about evaluation and false-positive rates. - Docker and containerization experience, including image optimization, ECR, and stateless worker design. - Ability to operate fully independently — no engineering team underneath you — while documenting continuously and coordinating cleanly with an internal team. Nice to Have - Experience with API ingestion and field-level diff-detection systems. - Laravel or PHP familiarity, enough to coordinate cleanly on API contracts with the portal team. - SOC 2 Type II compliance experience. - Salesforce API integration experience. - Regulated-industry experience (financial services, healthcare, or insurance). Benefits - The expected hourly range for this position is $80/hr - 100/hr. This hourly range is an estimate, and the actual hourly rate may vary based on the Company’s compensation practices. - The hourly rate may be adjusted based on applicant's geographic location. - This position is eligible to participate in the Company’s standard employee benefits programs, which currently include health care benefits. Company Description QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law. Please see QuinStreet’s Employee Privacy Notice here.
• Design, build, and maintain AI agents, integrations, and automations that reduce manual work, eliminate bottlenecks, and improve productivity across every department at Chipply. • Inspect Chipply's internal SaaS platforms (HubSpot, Microsoft 365, Confluence, Slack, and others) to understand what APIs, webhooks, and MCP connectors they expose, and use those surfaces to build the integrations each team needs. • Partner with leadership and department heads to identify and prioritize high-impact opportunities by mapping existing workflows and pinpointing where engineering effort — AI-powered or deterministic — will deliver measurable improvement. • Write production code. Build multi-tool and multi-agent systems that connect Chipply's internal platforms into seamless end-to-end processes. Make sound judgment calls on when AI is the right tool and when a deterministic solution is a better fit. • Build evals and monitoring for AI systems you ship, so output quality is measurable rather than assumed. • Serve as Chipply's internal AI champion by leading education, training, and adoption efforts, and by acting as the go-to engineering resource for AI questions, best practices, and emerging use cases. • Establish and maintain responsible AI governance, including guidelines for data handling, privacy, model and tool selection, output quality monitoring, and ethical use. • Continuously evaluate emerging AI tools, agent frameworks, model providers, and orchestration libraries; pilot promising technologies and recommend adoption decisions based on impact, cost, and fit. • Measure and report on the ROI of the systems you ship, tracking time saved, error reduction, cost impact, and quality improvements. • Develop and maintain documentation for the systems, integrations, and AI workflows you build so institutional knowledge scales with the company. • Serve as a liaison across Engineering, Finance, Sales, Marketing, Customer Support, and Product to align on technology needs and ship workflow improvements end to end. • Monitor security and compliance across the integrations and AI systems you build, collaborating with engineering and leadership to ensure data protection best practices are followed. • Continuously redefine the scope, priorities, and deliverables of the role as Chipply's needs and the broader AI ecosystem evolve.
Bringing peace of mind through better health to our customers and communities
Role Description BlueCross BlueShield of Tennessee is seeking a Senior AI Engineer to lead the design, development, deployment, and support of advanced AI solutions across the healthcare payer ecosystem. As part of the MLOps team, this position operates at the intersection of AI engineering, MLOps, and applied business problem-solving. The Senior AI Engineer will help evaluate and adopt emerging AI platforms, shape how AI solutions are architected and delivered, and collaborate with cross-functional teams to bring production-ready solutions to life. This role also plays a key part in mentoring engineers and establishing best practices for modern AI development. Why This Role Is Exciting: - End-to-End Impact — Work across the full lifecycle, from use case discovery and prototyping to delivering enterprise-scale AI solutions - Hybrid AI Role — Engage across AI engineering, Generative AI, and MLOps in a single, high-impact position - Modern Technology Exposure — Work hands-on with LLMs, evaluation frameworks, observability tools, and cloud-native platforms - Cross-Functional Collaboration — Partner with business and technical stakeholders to solve real-world challenges - Influence & Ownership — Help define standards, delivery models, and enterprise AI architecture - Culture of Innovation — Thrive in an environment that encourages continuous learning, experimentation, and collaborative ideation Note: This is a fully remote role, but final interviews at our Chattanooga, TN headquarters will be required. Sponsorship is available for this role. Qualifications - Bachelor's degree in STEM (Science, Technology, Engineering or Math) or related field or equivalent work experience required. - Master’s or PhD degree in a relevant field (e.g., Computer Science, AI, Machine Learning) strongly preferred. - 5+ years of relevant work experience in analytics, technology, software engineering, or healthcare (academic experience included), or related equivalent experience. - 3+ years of hands-on experience specifically with machine learning, deep learning, and preferably AI models (e.g., LLMs, diffusion models) is required. - Proven experience handling large, complex datasets to build and optimize sophisticated data science pipelines. - Deep experience with Machine Learning, Deep Learning frameworks (e.g., Pytorch, TensorFlow), Natural Language Processing (NLP), and associated libraries (e.g., Hugging Face Transformers). - Experience deploying and managing ML models in cloud environments (GCP Vertex AI preferred, AWS SageMaker or Azure ML acceptable). Requirements - Expert proficiency in Python and relevant data science/ML libraries. - Proficient in Microsoft Office (Outlook, Word, Excel, and PowerPoint). - Proven ability to architect, design, and implement complex systems. Demonstrated success leading technically challenging projects from conception through to deployment. - Exceptional ability to interpret and translate complex technical concepts into information meaningful to project team members, business personnel, and leadership. - Strong technical leadership and mentorship capabilities. - Must be able to communicate effectively and influence both technical and non-technical co-workers and stakeholders. - Highly organized, reliable, capable of managing multiple complex tasks, demonstrating an exceptional work ethic and strategic thinking. Company Description
Role Description Tealium is seeking a Senior Engineer, AI Developer Tools, to contribute to the vision, design, and rollout of our next-generation AI-driven developer tools. This is a high-impact role at the core of a strategic initiative to modernize Tealium’s engineering ecosystem, enabling teams with intelligent, automated, and scalable tooling. In this role, you will directly empower Tealium’s development teams to innovate faster, enhance code quality, and dramatically increase engineering productivity through AI. This is a unique opportunity to lead a critical strategic initiative, influence technical direction, and help teams adopt AI-forward development practices in a measurable, practical way across the engineering organization. As the driving force behind AI Developer Tools, your work will accelerate both engineering and business velocity by: - Accelerating Product Modernization, Engineering Velocity and Quality: Designing, building, and owning internal AI-driven developer platforms and tools (such as code review, test generation, migration automation, and CI/CD copilots) to achieve measurable improvements in engineering productivity and code quality. - Defining evaluation frameworks, orchestration, and governance (guardrails) for integrating AI safely into the developer workflow to tackle technical debt and accelerate modernization initiatives (e.g., AWS SDK migrations, Java 21 upgrades). - Leading a critical strategic initiative, influencing technical direction, and helping teams adopt AI-forward development practices. Qualifications - 5+ years of software engineering experience, with at least 3 years leading large-scale internal tooling, platform engineering, or modernization efforts. - Proven success designing and delivering AI-powered developer tools—beyond experimentation—with real-world measurable impact on team velocity and quality. - Deep understanding of modern software development practices, languages, and environments (e.g., Java, TypeScript, CI/CD, cloud infrastructure). - Experience using strategic thinking to drive solutions for complex, undefined problems within enterprise-scale engineering organizations. - Strong architecture and system design skills, with the ability to make build-vs-buy decisions and scale tooling across organizations. - Demonstrated ability to influence with authority, collaborate across disciplines, and lead by example in a senior or principal engineering capacity. - Exceptional cross-functional communication skills, including the ability to clearly present complex technical concepts and translate engineering efforts into business value. - A passion for improving the developer experience and a practical mindset toward applying AI to solve real engineering problems. - Experience evaluating AI tools and models across critical dimensions, including quality, cost, latency, security, and workflow fit. - Familiarity with tools like Claude Code, GitHub Copilot, AWS Q, or other generative AI platforms. - Experience applying AI/automation to software development workflows with measurable improvements in speed, quality, or reliability. Requirements - Drive AI-Powered Refactoring of Monolithic Platform Components. - Design and Implement AI-Enhanced Code Review and Test Automation. - Lead Measurement and Adoption of AI Tools. - Evaluate and integrate best-in-class AI technologies. - Establish and scale repeatable AI-assisted development workflows. - Serve as a technical authority and thought leader across the engineering organization. - Drive large-scale modernization initiatives. - Stay current with emerging AI and developer productivity trends. - Articulate technical vision and strategic decisions to senior stakeholders. - Drive multi-week implementations of AI-powered developer tools. Benefits - Employees are eligible to receive an annual bonus and stock options. - Employees and their families are eligible for medical, dental, vision, life, and disability insurance. - Employees have the option to enroll in our 401k plan and are eligible for contributions for company matching. - Employees are eligible for flexible paid time-off and extended paid parental leave. - We offer 11 paid holidays annually with an additional Healium Be-Well break for most employees. - We offer 15 hours of paid work time for volunteer activities and programs. - Sick leave accrual varies by employee classification and location. Wage Transparency The U.S. pay range for this full-time position is $145,000 - $185,000 + Variable + Equity Options. Base pay offered may vary depending on job-related knowledge, skills, and experience. Why You Want to Work Here - Tealium WOWs (Ways of Work), our award-winning culture. - Mosaic, our commitment to diversity, equity, and inclusion. - Tealium Cares, promoting caring in our communities. - Tealium Connects (remote-first working). - Tealium Ownership, share in the success of Tealium. - Tealium Time, paid time-off policy for flexibility. - Healium, health and wellness programs. - Tealium LIFT (Learning is Facilitated at Tealium), offering professional development opportunities. - Health and Related Benefits Programs, offering market competitive benefits.
Role Description Reporting to the Director of AI Engineering, the Lead AI Engineer is responsible for building, managing, and scaling Gifthealth's AI engineering function. This position combines hands-on technical work with team leadership: architecting and implementing agentic AI systems while building, developing, and leading a team of AI Engineers. The Lead AI Engineer drives technical decisions across LLM orchestration, RAG pipelines, and production AI infrastructure, while establishing engineering practices, R&D functions, and growing team capabilities. We are seeking a Lead AI Engineer to partner with ML Engineers, Prompt Engineers, and Product teams, ensuring alignment with organizational goals, operational excellence, and compliance standards. Key Responsibilities - Designs and builds agentic AI systems including LLM orchestration, RAG pipelines, and multi-agent frameworks - Leads, mentors, and grows AI Engineers, conducting one-on-one meetings, performance reviews, and identifying career development opportunities - Works with the Talent Acquisition team to recruit and hire AI Engineers through defining role requirements, screening candidates, and leading technical interviews - Establishes engineering practices, coding standards, and technical processes for AI systems - Partners with ML Engineers, Prompt Engineers, and Product on cross-functional AI initiatives - Drives build/buy/integrate decisions; evaluates AI tooling and vendor solutions Qualifications - Bachelor’s degree in computer science, AI/ML, or a related field OR 2–4 years of equivalent practical experience (Required) - Master’s degree in computer science or AI/ML (Preferred) - 6+ years of software engineering experience with 3+ years in AI/ML systems; 2+ years of management or tech lead experience; history of building and shipping production AI systems (Required) - Experience in healthcare or regulated industries; history of building teams from scratch; FDA or clinical trial software experience (Preferred) - Knowledge of LLM architectures and orchestration patterns; RAG systems and vector databases; production AI/ML system design; software engineering best practices; and leadership and management principles (Required) - Knowledge of the healthcare domain and HIPAA compliance; FDA software validation; human-in-the-loop ML systems; graph databases and knowledge graphs (Preferred) - Python and AI/ML development skills (Required) - LLM API integration skills (Required) - System architecture and design skills (Required) - Technical hiring and interviewing skills (Required) - Team leadership and mentorship skills (Required) - GPU-accelerated processing skills (Preferred) - Distributed systems skills (Preferred) - Cloud platform (AWS, GCP) skills (Preferred) - ML Ops tooling skills (Preferred) - Ability to balance hands-on building with team leadership (Required) - Ability to hire and develop engineering talent (Required) - Ability to drive technical decisions across teams (Required) - Ability to communicate with technical and non-technical stakeholders (Required) - Ability to navigate ambiguity in early-stage product development (Preferred) - Ability to establish engineering culture and practices from scratch (Preferred) - Ability to influence without authority across functions (Preferred) Work Environment - Location: Remote - Schedule: 8:00 A.M. to 5:00 P.M. Monday through Friday with night and weekend hours on occasion as determined by the needs of the business. - Regular meetings with internal AI Engineering, Prompt Engineering, ML Engineering, Software Engineering, ML Ops Engineering, Data Science, HR, and product management teams. This role may also have meetings with AI/LLM, cloud, and ML Ops vendor and technology partner representatives. - Must be able to remain in a stationary position for extended periods while writing or reviewing documentation - Must be able to work on a computer for the entire shift - Must be able to attend virtual meetings with cross-functional teams Employment Classification - Status: Full-time - FLSA: Exempt Equal Employment Opportunity (EEO) Statement Gifthealth is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. All employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, transgender status, national origin, age, disability, veteran status, or any other legally protected status. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you do not meet every requirement but still feel you would be a great fit for this role, we encourage you to apply! Disclaimer This job description is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all responsibilities, duties, or skills required of personnel. Gifthealth reserves the right to modify job duties or descriptions at any time.
Louco is the game changer in live entertainment. The first platform that truly understands what users want and delivers hyper-personalized event experiences.
Role Description At Louco, we’re reinventing how people find and experience events. We’re looking for a Full Stack Engineer to join our small, fast-moving team and help build the future of event discovery. - Build and scale full stack systems powering Louco’s event discovery platform — from backend infrastructure and APIs to intuitive frontend user experiences. - Own end-to-end user flows across the platform, ensuring users can seamlessly discover, explore, and attend events. - Develop and improve systems for personalized feeds, recommendations, venue discovery, notifications, search, and ticket integrations across multiple providers. - Help integrate AI into the product experience to improve discovery, personalization, recommendations, and content understanding. - Build scalable ticketing and checkout-related systems connecting users with events in the fastest and simplest way possible. - Collaborate closely with engineers, product, and design to turn ideas into fast, intuitive, and scalable product experiences. - Take ownership of features from idea to production — including architecture, implementation, testing, deployment, and performance optimization. - Improve platform scalability, reliability, and app performance as Louco continues to grow. - Work in a fast-moving startup environment where priorities evolve quickly and new challenges constantly emerge. - Help shape the future of how people discover and experience real-world events. Qualifications - You’re a strong full stack engineer who enjoys building scalable product experiences across frontend and backend systems. - You’re highly proficient with technologies like PHP/Laravel, React, Node.js, and TypeScript. - You actively use AI development tools like ChatGPT, Claude, Cursor, Copilot, or similar tools to move faster and work smarter. - You enjoy building end-to-end user experiences and can move seamlessly across product, backend, infrastructure, and integrations. - You move fast, stay calm under pressure, and are able to make smart and pragmatic decisions in fast-changing environments. - You care about clean architecture, scalability, performance, and building products with real user impact. - You take ownership, think independently, and enjoy solving difficult problems with limited resources. - You’re excited about helping reinvent how people discover and experience real-world events. Benefits - Performance-based bonuses for outstanding contributions - High ownership and real product impact - Work directly with the founders - Build the future of event discovery - Flexible remote work - Opportunity to grow with the company long term - Work with modern AI tools and workflows Company Description Louco is the game changer in live entertainment. The first platform that truly understands what users want and delivers hyper-personalized event experiences.
Patch Management That Just Works | Real-time discovery and remediation of third-party and OS vulnerabilities
Role Description We are looking for a Applied AI Engineer to build and operate LLM-powered internal solutions, tools, automations, and customer-facing AI features end-to-end. We are not building AI for the sake of AI, or to follow hype or impress investors. We care about AI that works in real life and solves actual problems. Technology choices and product decisions are not simply handed down from the top. You will have room to shape the solution, challenge assumptions, choose the right tools, and influence the result. - Build and operate LLM-powered internal solutions, tools, and automations end-to-end - Ship customer-facing AI features - Drive technical decisions from design through production rollout - Own systems in production, including monitoring, reliability improvements, and incident response participation - Build and maintain LLM evaluation workflows, including quality/safety checks, baselines, and regression detection - Partner with R&D, product, and security teams - Evaluate emerging AI technologies and patterns, and advocate adoption when justified Qualifications - Strong software engineering fundamentals with hands-on ownership of production systems; Python required - Solid LLM application development experience, including context design, structured outputs, and orchestration - Hands-on experience with LLM evaluations, including experiment design, regression detection, gating, and observability - Experience building and operating backend services/APIs in production - Experience designing multi-service architectures and reliable integrations, including stable service contracts, retries, and failure recovery - Working knowledge of operating production databases, including schema design, indexing, migrations, and backup/restore - Hands-on experience with containerized workloads - Ability to balance output quality, latency, and cost in production AI systems Requirements - Experience with agentic systems or RAG, including evaluation - Experience building lightweight user interfaces - Experience shipping high-adoption internal developer or operations tooling - JavaScript/TypeScript - AWS deployment and operations experience - Experience with runtime isolation and sandboxing for sensitive execution - Experience in B2B SaaS, security, compliance, or data governance contexts Technology we use You do not need to have experience with every tool listed below, but this is the environment we work with now: - Python, uv, FastAPI, PydanticAI - PostgreSQL, Docker, Docker Compose - AWS: EC2, ECR, S3, Lambda - Interfaces and tooling: Streamlit or similar tools, pytest, ruff, pyright, OpenTelemetry Benefits - Fully remote work, giving you the flexibility you need in the modern world - A collaborative environment encouraging you to own your domain and implement best practices - Stable income, benefits, flexible working hours, and opportunities for promotion - Friendly and professional peers, eager to help and help you grow - A multitude of interesting challenges and opportunities
The #1 Converged Identity Platform with Intelligent Access Governance for Employees, Third Parties & Machines.
• Identify and prioritize high-impact AI use cases across Customer Office teams in partnership with Revenue Operations. • Design and implement AI-driven workflows and agentic solutions across the Customer Office tech stack. • Build and scale automation and intelligence layers on top of Salesforce and the broader GTM stack. • Serve as the AI expert, partnering with Enterprise Systems and Architecture teams to define and enforce data models. • Leverage Customer data to power AI-driven insights and workflows. • Stay ahead of AI and GTM technology trends by rapidly evaluating and testing new tools and approaches.
Building mobile RPG Games with AI ✨ Companions 🤖. First game: Hell Rush is coming in July 2024.
• Agent orchestration frameworks for multi-step reasoning, tool use, and constraint-based problem solving across banking workflows • RAG pipelines covering embedding generation, chunking, hybrid retrieval, and retrieval evaluation, calibrated for banking document types • LLM integration layers connecting banking models, APIs, and knowledge bases into reliable, auditable inference workflows • Evaluation infrastructure including behavioral contracts, regression baselines, and production observability for non-deterministic AI outputs • Backend services and APIs powering client-facing AI products at bank-tier uptime requirements
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Python, TypeScript, GraphQL, JavaScript, Distributed Systems, Azure
