| Location | San Francisco, California |
| Website | https://www.getclera.com/ |
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.
Design, build, and maintain agentic systems that automate complex, multi-step workflows across regulated industries including healthcare, legal, fintech, logistics, and compliance.
Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure — vector DBs, 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: design APIs and data models, implement frontend and backend code, and operate production systems with CI/CD, monitoring, and testing.
Collaborate closely with founders, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry.
Must-haves:
2+ years of software engineering experience with a track record of shipped, user-facing or backend products.
Hands-on experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration.
Full-stack proficiency: Python plus TypeScript/React (or equivalent); experience with 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.
Experience designing API-driven, high-throughput systems and real-time product features.
Nice-to-haves:
Experience with agent or workflow frameworks (e.g., LangGraph, CrewAI) and orchestration tools (e.g., Temporal, Trigger).
Background building multi-tenant or enterprise-ready systems, or prior experience in regulated industries (healthcare, fintech, legal).
Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration.
Up to 8 years of total engineering experience — seniority range is wide; ownership mindset matters more than years.
Salary: $180,000 – $400,000 USD annually (range reflects experience and equity mix)
Early-stage equity in a pre-seed company with strong investor backing
Visa sponsorship: Not available
This is an on-site role based in San Francisco, CA. Candidates must be willing to work from our San Francisco office.