Full-Stack Engineer, Agent Evaluation & Reliability
True Talent Solutions Partners · San Francisco · onsite
ABOUT THE ROLE
Join a seed-stage AI infrastructure startup building systems that help enterprise AI agents become more reliable. This backend-leaning full-stack role focuses on the data models, integrations, and workflows that turn agent performance signals into continuous product improvements.
WHAT YOU'LL DO
- Build and operate backend systems for agent evaluation and continuous improvement.
- Design data models for evaluation datasets, experiment runs, agent traces, knowledge versions, findings, and customer-defined quality criteria.
- Develop and maintain enterprise integrations, including authentication, OAuth, webhooks, syncs, backfills, retries, and monitoring.
- Own features from technical design and implementation through deployment, production monitoring, customer feedback, and iteration.
- Work with customers to understand their systems, diagnose failures, and turn specific needs into reusable product capabilities.
- Ship full-stack features that make the platform's underlying infrastructure useful to customers.
WHAT WE'RE LOOKING FOR
- Two to four years of experience building and operating production software, including experience at a fast-paced startup.
- Hands-on machine learning engineering and model development experience, with an understanding of how evaluating nondeterministic agent systems differs from conventional testing.
- Strong production experience with TypeScript and Node.js or Bun, and the ability to work across the full stack.
- Strong PostgreSQL skills and practical experience with Redis, job queues, background workers, or workflow systems.
- Experience owning projects end to end, moving quickly, and making sound technical and product decisions.
COMPENSATION & BENEFITS
Base salary: $120,000 to $180,000 annually. Visa sponsorship is available.
LOCATION
On-site in San Francisco, California, United States.