AI Engineer (Mid-Level)

ABOUT THE ROLE This is a mid-level AI Engineer role on the core product team, focused on building agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. You'll work across the full stack to ship production LLM-based services, ensure reliability and safety, and collaborate with leadership, product, and design to deliver measurable user impact. WHAT YOU'LL DO - Design, build, and maintain agentic systems that automate complex, multi-step workflows across healthcare, legal, fintech, logistics, and compliance domains. - Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure including vector databases, embeddings, and indexing for domain-specific search at scale. - Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences. - Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability. - Ship full-stack AI products from MVP to enterprise-grade by designing APIs and data models, implementing frontend and backend code, and operating production systems with CI/CD, monitoring, and testing. - Collaborate with leadership, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry. WHAT WE'RE LOOKING FOR - 2–8 years of software engineering experience with demonstrated delivery of shipped user-facing or backend products. - Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration. - Proficiency across the stack: Python plus TypeScript/React (or equivalent), and experience with cloud platforms (AWS or GCP) and relational or NoSQL databases. - Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines, with sound judgment to choose appropriate approaches. - Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos. - Experience with agent or workflow frameworks and orchestration tools. - Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration. - Background building multi-tenant or enterprise-ready systems, or experience in regulated industries such as healthcare, fintech, or legal. - Experience designing API-driven, high-throughput systems and real-time product features. - Proven ownership delivering end-to-end features from data model to deploy and monitoring, with a user-centric and pragmatic engineering mindset. LOCATION Remote or San Francisco, CA, United States.