Full-Stack Engineer, Agent Evaluation & Reliability
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 23, 2026.
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.