Experience with agent-based systems and tool calling
Experience setting up guardrails, moderation, and safety checks
Familiarity with Docker, cloud infra, and CI/CD
Prior work in platform teams or enablement roles
Hands-on experience with LLM APIs (OpenAI, Anthropic, etc.)
Experience with RAG pipelines, embeddings, vector databases
Familiarity with prompt engineering, prompt versioning, and evaluation
Experience with AI orchestration frameworks
Good understanding of AI observability, cost monitoring, and failure modes
You’ve shipped at least one LLM-powered feature to production and iterated based on telemetry or user feedback
Comfortable with embeddings, fine-tuning, vector search, tokenisation, and evaluation methodologies
Familiar with data lakes/warehouses, feature stores, and streaming/batch ETL; cloud (AWS/GCP/Azure)
Excellent Python skills (required)
Experience building frameworks, platforms, or developer tooling
Strong understanding of APIs, services, and system design
Writes clean, maintainable, production-grade code