About the Role
We're a small, fast-moving team building the next generation of AI-driven products that automate complex, multi-step workflows across regulated and enterprise domains — think healthcare, legal, fintech, logistics, and compliance. As a Mid-Level AI Engineer on our core product team, you'll work across the full stack to ship production LLM-based services, own critical infrastructure, and collaborate directly with founders and product to deliver real, measurable user impact.
This is a high-ownership role on a lean team. You'll touch everything from data models and APIs to agent orchestration and evaluation infrastructure — and you'll see your work in the hands of users quickly.
What You'll Do
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Design, build, and maintain agentic systems that automate complex, multi-step workflows across regulated industries including healthcare, legal, fintech, logistics, and compliance.
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Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure — vector DBs, embeddings, and indexing — for domain-specific search at scale.
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Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences.
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Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability.
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Ship full-stack AI products from MVP to enterprise-grade: design APIs and data models, implement frontend and backend code, and operate production systems with CI/CD, monitoring, and testing.
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Collaborate closely with founders, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry.
What We're Looking For
Must-haves:
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2+ years of software engineering experience with a track record of shipped, user-facing or backend products.
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Hands-on experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration.
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Full-stack proficiency: Python plus TypeScript/React (or equivalent); experience with AWS or GCP and relational or NoSQL databases.
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Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines with sound judgment on when to apply each.
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Experience building automated tests, evaluations, and monitoring for AI systems to ensure production reliability beyond demos.
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Experience designing API-driven, high-throughput systems and real-time product features.
Nice-to-haves:
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Experience with agent or workflow frameworks (e.g., LangGraph, CrewAI) and orchestration tools (e.g., Temporal, Trigger).
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Background building multi-tenant or enterprise-ready systems, or prior experience in regulated industries (healthcare, fintech, legal).
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Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration.
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Up to 8 years of total engineering experience — seniority range is wide; ownership mindset matters more than years.
Compensation & Benefits
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Salary: $180,000 – $400,000 USD annually (range reflects experience and equity mix)
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Early-stage equity in a pre-seed company with strong investor backing
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Visa sponsorship: Not available
Location
This is an on-site role based in San Francisco, CA. Candidates must be willing to work from our San Francisco office.
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