We are looking for a Senior AI Platform Engineer to design, build, and operate a production-grade AI platform within a complex enterprise environment.
In this role, you will take end-to-end technical ownership of the AI platform, including AI gateway engineering, governance, agent management, access control, cost telemetry, observability, and developer enablement. This is a highly hands-on role for someone who has already built an AI governance/platform capability in production and can bring that experience into a new environment.
Key Responsibilities
Build and operate an enterprise AI Gateway, including SSO, request logging, data-classification tagging, policy enforcement, and model routing
Work with Azure OpenAI / AI Foundry, Entra ID, and Azure API Management (APIM)
Build and maintain a governed repository of approved AI agents, including ownership, permissions, and data scope
Develop cost telemetry to attribute AI usage to specific cost centres and use cases
Automate access provisioning and licence lifecycle management for enterprise AI tools
Develop reusable developer templates and golden paths for RAG, AI agents, and evaluation
Establish production observability, monitoring, and operational runbooks
Build and operate containerised workloads on Kubernetes
Implement identity and access controls including SSO, RBAC, and service principals
Build internal platform capabilities and developer services that can be adopted across engineering teams
Implement Infrastructure as Code and CI/CD practices for reliable platform delivery
Requirements
Previous hands-on experience building an AI governance/platform capability end-to-end in production
Ability to demonstrate a previous AI platform implementation, including what was built, what it governed, who used it, and lessons learned
Strong production experience with Kubernetes and containerised workloads
Hands-on experience with AI gateways / LLM proxies, such as APIM, Kong, LiteLLM, or equivalent
Practical experience developing LLM applications, including API integration, token/cost behaviour, evaluation, and RAG patterns
Strong production observability experience using OpenTelemetry, Grafana, Azure Log Analytics, or equivalent
Strong backend engineering skills in Go (preferred), Python, or TypeScript
Hands-on experience with Infrastructure as Code and CI/CD, including Terraform and GitHub Actions or Azure Pipelines
Strong experience with identity and access management, including SSO, RBAC, and service principals
Proven experience building an internal platform or developer service successfully adopted by other teams
Strong ownership, problem-solving, and independent working capabilities
Tech Stack
AI & Azure: Azure OpenAI, Azure AI Foundry, APIM Identity: Entra ID, SSO, RBAC, Service Principals
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