About the RoleThis is a mid-level AI Engineer position on the core product team at a pre-seed AI startup, building agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. You will work across the full stack to ship production LLM-based services, own reliability and safety infrastructure, and collaborate closely with founders and design to deliver measurable user impact.
What You'll Do- Design, build, and maintain agentic systems that automate multi-step workflows across domains such as healthcare, legal, fintech, logistics, and compliance.
- 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 founders, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry.
What We're Looking For- 2 to 8 years of software engineering experience with a track record of shipping user-facing or backend products, ideally in a startup environment.
- Hands-on production experience deploying LLM-based services, including prompt design, orchestration, and tool integration.
- Full-stack proficiency in Python and TypeScript/React (or equivalent), plus 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 on when to apply each.
- Experience building automated tests, evaluations, and monitoring for AI systems to ensure production reliability beyond demos.
- Familiarity with agent or workflow frameworks such as LangGraph or CrewAI, and orchestration tools such as Temporal or Trigger.
- Background in 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.
- An ownership mindset: comfortable delivering end-to-end features from data model to deployment and monitoring.
Compensation & BenefitsSalary range:
$180,000 to $400,000 USD annually (inclusive of equity component). Visa sponsorship is not available for this role.
LocationOn-site in
San Francisco, California, United States. Candidates should be able to work in-office or willing to relocate.
