Full Stack Engineer, Applied AI

Role Overview This confidential client is hiring a Full Stack Engineer, Applied AI to help build the intelligence layer of a platform that turns customer intent into real-world operational execution. This is an engineering-focused role that productizes frontier models into reliable production systems — agent loops, retrieval pipelines, internal tools, evals, observability, and end-to-end product workflows. This is not an ML research or model-training role; you will build AI systems that reason over operational context, dispatch work to human operators, detect and mitigate risk, and take action in the real world. What You’ll Do Build full-stack AI product features end-to-end across React, TypeScript, backend services, database schema, agent logic, and evals. Create agents that receive customer requests and dispatch operational work to appropriate human operators. Design and implement agent loops that plan multi-step actions, call internal tools, request help when needed, and recover when reality changes. Build retrieval and structured-context systems (RAG) that ground agents in operational data. Surface operational risks proactively and create automated or assisted remediation before issues impact customers. Instrument evals, monitoring, and production observability to measure agent quality and catch regressions. Iterate on prompts, tool definitions, model choices, and agent architecture using production telemetry. Partner closely with design and operations to decide what to automate, assist, or leave human-in-the-loop. Help define shared AI engineering patterns and best practices that future products can leverage. Who You Are 2+ years of full-stack engineering experience with strong product instincts and ownership from UI to backend to schema. Strong TypeScript experience across frontend and backend; experience with React and Node is expected. Practical experience shipping AI-driven product features in production (LLM APIs, prompting, retrieval, tool use, structured outputs). Working knowledge of retrieval-augmented generation (RAG), retrieval pipelines, agent patterns, and evaluation workflows. Experience with Postgres and Redis or similar databases/caches; comfortable designing schema and backend services. Strong judgment about what should be automated vs. assisted vs. human-in-the-loop. Comfortable handling messy, real-world workflows: noisy inputs, incomplete data, and systems coordinating human operators. Bias toward shipping, measuring in production, learning fast, and iterating quickly. Comfortable in an early-stage environment with ambiguity, autonomy, and limited process. Interest or experience with tools and platforms such as OpenAI, Anthropic, Claude, Cursor, Azure, custom agent loops, and AI-assisted development workflows. Bachelor’s degree or equivalent practical experience preferred. Compensation & Logistics Salary: $200,000 - $250,000 per year (base range; final offer may vary based on experience, location, and applicable state/local requirements). Employment type: Full-time. Workplace: Hybrid (San Francisco Bay Area). Visa sponsorship: This role offers visa sponsorship. This position is posted on behalf of a confidential client (the hiring organization will make final employment decisions). Equal Opportunity & Hiring Transparency CareerTakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making . Final hiring decisions are made by people. If you have questions about how your data is used, please contact us directly.