AI Systems Engineer
Mid-Senior / SeniorDesign and deliver production AI systems end-to-end, from agents and RAG pipelines to AI-supported automation integrated into real product workflows.
Core Requirements
- Strong foundations in Python and backend engineering
- Hands-on experience with LLM applications, agent orchestration, and tool/API integration
- Practical knowledge of RAG: ingestion, retrieval, evaluation, and quality iteration
- Experience integrating AI systems into existing products and internal tools
- Production mindset: reliability, traceability, security, and cost awareness
- Comfortable with ambiguity, rapid iteration, and end-to-end responsibility
Nice-to-haves
- MCP and tool ecosystems for agents
- Fine-tuning custom models or domain-specific ML pipelines
- Experience with planning and optimization (scheduling, routing, resource allocation)
- Vector databases and evaluation frameworks