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Senior Applied AI Engineer
Skills
Agentic WorkflowsLanggraphLarge Language ModelsMCPMlopsMulti-Agent SystemsPython
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Shipped at least one production LLM or agent system used by external users at meaningful scale
- Strong production Python coding ability
- Direct experience with multi-agent systems RAG and at least one agent framework in production
- Built evaluation infrastructure yourself
- Uses AI coding agents daily in real workflow
- Can operate as a founding IC with high ownership autonomy and speed
Nice to have
- High ownership
- High autonomy
- Comfort with ambiguity
- Fast paced
Day to day
- Build production LLM applications and multi-agent systems for real external users at scale
- Design and improve RAG pipelines and retrieval systems for large messy real-world data
- Develop agent orchestration with tool use memory and reliability engineering
- Create evaluation harnesses including regression suites LLM-as-judge and golden sets
- Define the reference architecture and engineering standards for a growing applied-AI team
Hiring process
- Two-stage interview process
- Moving quickly