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

Backend: Go, Python, TypeScript
Platform: Kubernetes, Containers
AI Gateway: APIM, Kong, LiteLLM or equivalent
Observability: OpenTelemetry, Grafana, Azure Log Analytics
Infrastructure & CI/CD: Terraform, GitHub Actions, Azure Pipelines
AI Engineering: LLM APIs, RAG, Agents, Evaluation

You will be a great candidate for us if you

• Have already built and operated an enterprise AI platform rather than only experimented with AI technologies
• Can take end-to-end technical ownership with a high degree of independence
• Understand both AI engineering and production platform engineering
• Build platforms and developer services that other engineering teams want to use
• Can balance governance, security, cost control, and developer experience
• Are comfortable making technical decisions in complex enterprise environments

Benefits

Why join inventYOU

• Build and shape enterprise-scale AI platform capabilities
• Work hands-on with modern Azure and Generative AI technologies
• Take ownership of technically complex and business-critical solutions
• Work across AI engineering, cloud, platform engineering, security, and DevOps
• Contribute to the adoption of AI across large-scale enterprise environments