
Affirm
Mid
Build production AI agents on Affirm's internal platform that serve 2,000+ employees across the People function
Affirm's People Tech & Analytics team is hiring a hands-on engineer to design, ship, and operate AI agents/APIs on Snowpark Container Services, integrating with Workday, Notion, and case tools while navigating existing RBAC/data-governance constraints. Expect deep questions on production ownership, LLM reliability engineering, and translating messy stakeholder requirements into shipped systems.
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What this interview tests
- Full-lifecycle ownership: architecture through production
- LLM reliability engineering (validation, fallback chains, circuit breakers)
- Integrating AI with governed enterprise data under RBAC constraints
- Translating ambiguous business requirements into production systems
- Python, CI/CD, containerization, monitoring
- Working across technical-business boundary with stakeholders
Common question themes
Describe building and deploying a production AI agent/application end-to-end with no spec
Design reliability infrastructure for a multi-model LLM service (fallback chains, circuit breakers, hallucination detection)
How would you ensure an AI system surfaces answers from governed content instead of guessing
Navigating RBAC/data governance across multiple systems for a people-data AI tool
Translate a vague business problem from a non-technical stakeholder into an architecture decision
How you diagnose and fix a production issue you own end-to-end
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