AI Engineer - LLM Adoption Department (LLMAD)
Core
Build and embed agent workflows and integrations for in-house LLMs within business units, replacing third-party alternatives.
Role type
Applied LLM engineer (agentic workflows)
Builds
Production agent workflows, tool-use integrations, and feature migrations to in-house models
Domain
AI / Large Language Models / Enterprise Software
Deliverable
production ML models
Required skills
Agentic engineering (tool/function calling, orchestration), Prompt engineering (structured outputs, versioning), Backend development (Python/Java/Go), API integration, Model evaluation, Debugging LLM failures
Preferred skills
Retrieval-augmented generation (RAG), LLM observability tooling, Self-hosted inference (vLLM), Cloud model deployment
Technologies
vLLM, Open-source LLMs, Orchestration frameworks
Responsibilities
Implement agent and tool-use workflows in business unit codebases, Debug and optimize latency/cost of LLM features, Run task-level evaluations and maintain eval harnesses, Design and iterate prompts and output schemas, Support migrations from third-party APIs to in-house models, Document reusable recipes and templates for team adoption
Seniority
Mid-level, hands-on IC
