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Roles & experience levels

6 roles across 4 experience levels. 167 tagged questions. Pick the slice that matches where you are in your career.

Roles

Builds production GenAI applications: prompting, RAG, agents, fine-tuning, inference cost and latency tradeoffs.

Specializes in retrieval-augmented systems: chunking, retrieval, reranking, vector DBs, RAG eval.

Integrates AI into product surfaces: UX flows, streaming, latency budgets, fallbacks, API contracts.

Works on the science: papers, theory, training dynamics, novel architectures, scaling laws.

Serves, scales, and monitors LLM systems: capacity, latency, observability, rollouts, on-call.

Owns AI feature strategy + roadmap: evaluation, ROI analysis, vendor selection, success metrics.

First AI role, conceptual depth and fundamentals matter most.

2-5 years experience, expected to design + ship features end to end with light supervision.

Architecture + scaling + technical leadership for AI systems.

Backend / DS / SRE ramping into AI: needs accelerated fundamentals + production lens.