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Salary
$150k – $250k per year
Location
In office (San Francisco)
Employment
Full-Time
Overview
Company
Impact
Profile match
Clera is a San Francisco company that runs an AI recruiting platform positioned as a talent agent rather than a job board, matching engineers and other technical candidates to roles at venture-backed startups. Its system reads a candidate's background and preferences, then represents them to hiring teams at companies funded by firms such as Andreessen Horowitz, Y Combinator, Index Ventures and General Catalyst, compressing the introduction step that traditional headhunting handles manually. The model is aimed at the segment where recruiter fees are highest and candidate supply is thinnest, and the platform handles screening, scheduling and pipeline tracking for both sides of the match.

About the Role

You will own the agentic infrastructure at a seed-stage AI startup building the foundational layer for AI-native service operations. This means designing and shipping the systems that let agents execute reliably in production, retain months of client context, and know when to hand off to a human. This is a foundational engineering role at a very early team, with outsized scope and impact from day one.

What You'll Do

  • Build and maintain core infrastructure that enables agents to execute tasks reliably across dozens of iterations.

  • Design and implement memory systems that retain months of client context from messy, real-world operational data.

  • Develop eval harnesses that teams actually trust to make production shipping decisions.

  • Own the full loop: build it, measure it, break it, fix it, and make it learn.

  • Ship agent systems for real customers and iterate directly based on production feedback.

  • Contribute across infrastructure, orchestration, customer collaboration, and early hiring as the team grows.

What We're Looking For

  • 3+ years shipping LLM agents that ran unattended in production for real users, with a clear understanding that the model is the easy part.

  • Hands-on experience building eval harnesses that were actually used to make production deployment decisions.

  • Experience with retrieval and memory systems that work on real, messy operational data, not demo RAG pipelines.

  • Strong Python proficiency for building production systems end to end.

  • Experience with agent orchestration, workflow management, or reliability patterns such as failure recovery and retry logic.

  • Experience building agent tooling, frameworks, or libraries is a strong plus.

  • Experience with human-in-the-loop or approval workflow systems is a plus.

  • Track record of intensity and execution: you force things into existence; open-source contributions or a founded technical project are a bonus.

Compensation & Benefits

  • Base salary: $150,000 to $250,000 USD annually.

  • Meaningful early equity.

  • Relocation assistance provided.

  • Visa sponsorship available.

Location

On-site in San Francisco, CA, United States.

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