Mid-Level AI Engineer
Summary
Clera is hiring a mid-level AI engineer on-site in San Francisco to build production agentic LLM systems that automate multi-step workflows in regulated domains. Day to day: RAG pipelines, multi-agent orchestration, evals and safety tooling, and full-stack delivery with Python, TypeScript/React, and cloud platforms like AWS or GCP.
About the Role
Join a core product team building agentic systems that automate complex workflows across regulated and enterprise domains. You will ship production LLM-based services and help make them reliable, safe, and useful for customers.
What You'll Do
Design and maintain agentic systems for multi-step workflows across areas such as healthcare, legal, fintech, logistics, and compliance.
Build production retrieval-augmented generation pipelines and retrieval infrastructure, including vector databases, embeddings, and indexing.
Implement multi-agent orchestration, tool calling, memory, and reasoning components.
Develop evaluation and safety tools to measure model performance, detect regressions, and support reliable production use.
Deliver full-stack AI features, from APIs and data models through frontend and backend implementation, testing, deployment, and monitoring.
Work with product and design partners to set priorities and success metrics, then improve features using user feedback and telemetry.
What We're Looking For
Two to eight years of software engineering experience delivering user-facing or backend products, including production engineering experience in a product-focused environment.
Practical experience deploying LLM services in production, including prompt design, orchestration, and tool integration.
Proficiency with Python and TypeScript/React or equivalent, plus cloud platforms such as AWS or GCP and relational or NoSQL databases.
Working knowledge of RAG, vector databases, embeddings, and retrieval pipelines.
Experience building automated tests, evaluations, and monitoring for production AI systems, as well as API-driven, high-throughput systems and real-time features.
Familiarity with agent or workflow frameworks such as LangGraph or CrewAI, and orchestration tools such as Temporal or Trigger.
Experience with multi-tenant or enterprise systems, or regulated domains such as healthcare, fintech, or legal; familiarity with fine-tuning or multimodal models is also useful.
A completed university degree and a track record of owning features from data model through deployment and monitoring.
Compensation & Benefits
Base salary: $150,000 to $180,000 annually. Visa sponsorship is not available.
Location
On-site in San Francisco, California, United States.
Skills
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