Founding Engineer, Agentic Systems

CLERA, LLC
San Francisco, CA, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$150,000.0 - $300,000.0
Working hours
Regular working hours
Job source

Tech stack

PostgreSQL Software Engineering TypeScript Large Language Models Prompt Engineering Agentic-AI Information Technology

Job description

Join the engineering team at an agentic integration platform for real-world operations and own the agent layer end to end. You will build production systems that help agents understand undocumented environments, recover from failures, and improve through accumulated knowledge. What You’ll Do

  • Build context and self-learning systems that improve agent performance as they encounter more integrations.
  • Develop self-healing workflows that detect production failures, diagnose causes, and recover autonomously.
  • Own the agent harness and meta-harness, enabling teams to build, evaluate, and evolve agents quickly.
  • Set engineering patterns for building, measuring, and improving agents across the platform.
  • Work closely with company leadership, experiment rapidly, and help grow the team responsible for agentic systems.

Requirements

  • Two to nine years of professional software engineering experience, with recent experience building agentic software.
  • A completed or in-progress engineering, computer science, or quantitative degree from a top-250 technical university; a top-50 university is strongly preferred.
  • Experience as a founder of a startup that raised outside funding or hired a full-time employee, or as an engineer at a pre-seed, seed, or Series A startup backed by a top-tier venture firm.
  • Hands-on experience with context engineering, reusable agent harnesses, agent tracing, evaluations, and production failure detection, diagnosis, or recovery.
  • Experience shipping working production systems, rather than research alone. Familiarity with TypeScript, Effect-TS, PostgreSQL, LLMs, and agent evaluation is relevant.

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