AI Engineering Manager

Overview

As an AI Engineering Manager, you will design and drive the delivery of a scalable agentic AI strategy within Azure, leading end-to-end engineering of AI services. You’ll oversee multi-agent systems, orchestration, and LLM-powered applications, ensuring production readiness with observability and cost optimization. You will shape AI workflows, governance, and security while mentoring high-performing teams and collaborating with product and leadership to advance the AI roadmap.

Responsibilities

• Design and deliver scalable AI systems across Azure (Azure OpenAI, AKS, API Management, CosmosDB, Service Bus)
• Lead end-to-end engineering lifecycle: architecture, build, deployment, and optimisation of AI services
• Drive adoption of modern AI patterns (RAG, agent orchestration, event-driven workflows)
• Oversee multi-agent development, context/memory strategies, and auditability
• Embed secure-by-design principles and governance across AI workloads
• Partner with Safety and Compliance to enforce standards (OWASP GenAI, NIST AI RMF, ISO/IEC 42001)
• Lead CI/CD automation, IaC (Bicep/Terraform), and containerised deployments
• Mentor and scale AI engineering teams, set engineering standards, and manage complex technical challenges
• Translate business problems into AI-driven solutions and contribute to AI roadmap and investment planning
• Communicate progress, risks, and outcomes to senior stakeholders
• Ensure production readiness, observability, resilience engineering, and cost efficiency

Key requirements

• 5+ years in senior engineering roles with team leadership experience
• Hands-on experience with Azure AI ecosystem (Azure OpenAI, AI Foundry, Cognitive Services)
• Experience building and scaling distributed, cloud-native systems (AKS, microservices, APIs)
• Experience with LLM design: RAG, prompt engineering, orchestration frameworks
• Proficiency in Python, PowerShell, REST APIs, IaC
• Understanding of data platforms (CosmosDB, SQL, Redis) and event-driven architectures
• Experience designing/deploying multi-agent or autonomous AI systems
• Familiarity with real-time AI (voice, streaming, event-based processing)
• Understanding of AI evaluation, testing, red-teaming, governance and safety frameworks
• Ability to deliver complex platforms from concept to production and operate in fast-paced environments
• Strong stakeholder management and communication skills
• Certifications in Azure AI or cloud areas (Desirable)

• Collaborative and transparent
• Outcome-driven and pragmatic
• Strong communication with technical and non-technical stakeholders
• Azure OpenAI
• AI Foundry
• Cognitive Services

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