# AI Engineer (Mid-Level) at Clera

AI Engineer (Mid-Level) at Clera in San Francisco. On-site, full-time, paying $180k–$400k. Posted June 3, 2026.

- Company: Clera
- Location: San Francisco
- Workplace: On-site
- Job type: Full-time
- Pay: $180k–$400k
- Experience: 2+ years
- Posted: 2026-06-03
- Apply: https://jobs.ashbyhq.com/clera/12f95e17-702b-45eb-bb62-50d154401f8c/application
- Source: https://jobmagic.ai/jobs/ai-engineer-mid-level-clera-9542wq

## Requirements

- 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), 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 approach.
- Experience building automated tests, evaluations, and monitoring for AI systems to ensure reliability beyond demos.
- Experience designing API-driven, high-throughput systems and real-time product features.

## Description

### About the Role

Join a fast-moving, pre-seed-backed AI startup building the next generation of agentic systems that automate complex, multi-step workflows across regulated and enterprise domains — including healthcare, legal, fintech, logistics, and compliance. As a mid-level AI Engineer on the core product team, you'll own production LLM-based services end-to-end, collaborate closely with founders and product, and ship features that deliver measurable impact for real users.

### What You'll Do

- Design, build, and maintain agentic systems that automate complex, multi-step workflows across regulated industries.

- 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 — designing APIs and data models, writing 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

**Must-haves:**

- 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), 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 approach.

- Experience building automated tests, evaluations, and monitoring for AI systems to ensure 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).

- Familiarity with fine-tuning, parameter-efficient tuning, or multi-modal model integration.

- Background building multi-tenant or enterprise-ready systems, or prior experience in regulated industries such as healthcare, fintech, or legal.

### Compensation & Benefits

- **Salary:** $180,000 – $400,000 USD annually (reflecting a wide band across base and equity depending on experience).

- Early-stage equity in a venture-backed startup.