AI engineer roles
Every kind of AI engineer, on one marketplace.
12 roles across engineering, quality, reasoning, and product — from applied AI and forward deployed engineers to RAG builders, agent designers, and eval leads.
How to use this page
- Hiring teams — pick the role you’re hiring for, see the skills that actually matter, and search the marketplace for engineers who have them.
- Engineers — see what hiring teams expect from each role and the skills that prove you can do the work, then list yourself with those skills tagged.
- Beyond engineering — alongside core engineering we cover product, reasoning, and safety judgement, because shipping LLMs needs all of them.
Engineering
RAG Engineer
Builds retrieval-augmented systems over enterprise knowledge — ingestion, chunking, embeddings, retrieval, re-ranking, and grounded generation with citations.
Core skills
Agent / Tool-Use Engineer
Designs multi-step agent loops that pick the right tools in the right order, manage state, recover from failures, and stay within latency and cost budgets.
Core skills
LLM Fine-Tuning Engineer
Adapts open and closed models to a domain via SFT, LoRA/QLoRA, DPO/RLHF — owns dataset curation, training runs, and eval before shipping a checkpoint to production.
Core skills
Prompt Engineer
Turns fuzzy product requirements into prompts and chains that are measurably better — owns A/B prompt experiments, structured outputs, and guardrails.
Core skills
Applied AI Engineer
The generalist who ships LLM features end-to-end inside a product team — picks the right pattern (RAG, agent, prompt, fine-tune), wires it to the app, and owns the eval that proves it works.
Core skills
Forward Deployed Engineer
Embeds with a customer or design partner to ship a working AI solution against their real data and workflow. Bridges product, sales, and engineering — speed and judgement matter as much as code.
Core skills
LLM Systems / Inference Engineer
Owns the serving layer — throughput, latency, KV-cache, batching, quantization, and the cost-per-request that makes or breaks the unit economics.
Core skills
Quality
AI Evaluation Engineer
Designs the evals that decide whether a model ships. Builds rubrics, golden sets, and LLM-judge pipelines that catch regressions before users do.
Core skills
AI Safety / Red-Team Engineer
Stress-tests models and apps against jailbreaks, prompt injection, data exfiltration, and policy violations — and designs the mitigations that ship to production.
Core skills
Reasoning & Logic
LLM Reasoning Engineer
Builds the thinking layer on top of base models — chain-of-thought, planner-executor patterns, self-critique, and verifier-guided decoding for multi-step problems.
Core skills
Product & Strategy
AI Product Manager
Owns the AI roadmap end-to-end: scoping where LLMs add real value, sizing risk, picking eval bars, and translating model behavior into product decisions.
Core skills
Conversational UX Designer
Designs how the model talks: tone, turn-taking, repair flows, and the logic of when an agent should ask, defer, refuse, or hand off to a human.
Core skills
Don’t see your role?
The marketplace is shaped by what hiring teams actually need. If your team is searching for a role that isn’t listed — or you’re an engineer in a specialization we haven’t broken out yet — let us know.