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AI/ML Infrastructure Engineer

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Join an AI/ML engineering team building infrastructure for agent evaluation and continuous improvement. Build backend systems, data models, and enterprise integrations powering agent evaluation workflows. Requires 2-4 years of full-stack/backend experience with TypeScript, Node.js or Bun, and hands-on ML model development.

Key Highlights
Backend-leaning full-stack role on an AI/ML engineering team
Builds infrastructure for agent evaluation and continuous improvement
On-site in San Francisco, California
Visa sponsorship available (H-1B, OPT, O-1)
Salary $120,000-$180,000 annually
Key Responsibilities
Build backend systems that power agent evaluation and continuous-improvement workflows
Design data models for evaluation datasets, experiment runs, agent traces, knowledge versions, findings, and customer-defined quality criteria
Build and maintain enterprise integrations including authentication, OAuth, webhooks, incremental syncs, backfills, rate-limit handling, retries, and monitoring
Own features from technical design and implementation through deployment, monitoring, customer feedback, and iteration
Work with customers to understand their systems, diagnose failures, and turn specific needs into reusable product capabilities
Take features through the full stack while contributing to architecture and product decisions
Technical Skills Required
TypeScript Node.js PostgreSQL
Nice to Have
Experience with agent infrastructure, LLM evaluation, tracing, or agent memory systems in production or through substantial side projects

Job Description

About the Role

Join an AI/ML engineering team building infrastructure for agent evaluation and continuous improvement. This backend-leaning full-stack role combines foundational systems work with end-to-end product delivery, helping make agent workflows more reliable for enterprise customers.

What You'll Do

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