Netflix
Staff
Be Netflix Ads Platform's first dedicated AI engineer, building the agentic dev-workflow layer from zero
Netflix's Ads Platform Engineering team is hiring its first dedicated Staff AI Engineer to architect a centralized context layer and agentic workflows spanning code generation, PR review, incident triage, and multi-agent orchestration. This is applied AI on production infrastructure — not model training — for a team whose codebase is expanding fast and needs speed without accumulating slop or regressions.
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What this interview tests
- Agentic AI system architecture (context layer, multi-agent orchestration)
- Retrieval-augmented generation (indexing, embeddings, grounding)
- AI-integrated CI/CD (code gen, automated testing, PR pre-review)
- Operational AI tooling (incident triage, root cause analysis)
- Driving team-wide adoption of new AI-first workflows
Common question themes
Design a centralized context/knowledge layer for grounding AI coding agents
Describe a production agentic AI system you built — architecture, tools, evaluation
How do you balance AI-driven development speed against quality/regressions
A time you drove adoption of a new engineering workflow across a skeptical team
Your approach to multi-agent orchestration for parallel implementation/testing/docs
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