Senior AI Platform Engineer

Senior AI Platform Engineer

We're looking for a Senior AI Platform Engineer to design, build and operate the shared GenAI infrastructure that product teams rely on.

Key Responsibilities:

• Design, build and operate shared GenAI infrastructure: LLM routing, vector search and RAG infrastructure, MCP gateway, and AI observability/evaluation tooling.
• Apply strong distributed-systems fundamentals: async workflows, idempotency, failure design.
• Work hands-on with LLM APIs in production.
• Apply an AI-security mindset: prompt injection defenses, PII-in-logs handling, credential handling.
• Apply real engineering rigor to the Context Development Lifecycle (CDLD): generate, evaluate, distribute and observe the context that powers AI agents.
• Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
• Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).

Must-Have Skills:

• Kotlin or Python as primary proficiency, with comfort contributing to both.
• Experience designing/building/operating shared GenAI infrastructure: LLM routing; vector search and RAG infrastructure; MCP gateway; AI observability and evaluation tooling.
• Strong distributed-systems fundamentals: async workflows, idempotency, failure design.
• Hands-on production experience with LLM APIs.
• AI-security mindset: prompt injection, PII in logs, credential handling.
• Agent & harness engineering fluency, with concrete evidence of building/operating this kind of tooling, not just using it.
• Comfortable with the client's current daily tools: Claude Code and GitHub Copilot.

Nice-to-Have Skills:

• Specific cloud depth (AWS and/or GCP), Grafana, or named LLM API vendors. The RFP describes these capabilities generically rather than naming specific tools for this role — listed here as plausible, not confirmed.