AI Engineering Manager

Salary: £40,000 - 70,000 per year

Requirements:

• 5+ years in senior engineering roles, with experience leading technical teams.
• Strong hands-on experience with the Azure AI ecosystem, including Azure OpenAI, AI Foundry, and Cognitive Services.
• Proven expertise in building and scaling distributed, cloud-native systems, including AKS, microservices, and APIs.
• Experience with LLM application design, including RAG, prompt engineering, and orchestration frameworks.
• Proficiency in modern programming and automation, including Python, PowerShell, REST APIs, and IaC.
• Understanding of data platforms such as CosmosDB, SQL, and Redis, plus event-driven architectures.
• Experience designing and deploying multi-agent or autonomous AI systems.
• Familiarity with real-time AI, including voice, streaming, and event-based processing.
• Understanding of AI evaluation, testing, and red-teaming methodologies.
• Exposure to AI safety frameworks and governance models.
• Demonstrated ability to deliver complex platforms from concept to production.
• Experience operating in fast-paced, innovation-led environments.
• Strong stakeholder management and communication skills.
• Certifications are desirable, including Microsoft Azure AI Engineer Associate, Azure Solutions Architect Expert, or relevant AI/ML and cloud certifications.
• An engineering-first leadership style, with hands-on capability and technical credibility.
• An outcome-driven mindset focused on delivering measurable business value from AI.
• A pragmatic approach that balances cutting-edge innovation with operational stability.
• A security- and ethics-conscious mindset that prioritises responsible AI at scale.
• A collaborative and transparent approach that builds trust across technical and business teams.

Responsibilities:

• Support the design and drive the delivery of our agentic AI strategy.
• Lead the design and delivery of scalable AI systems across Azure, including multi-agent orchestration platforms and LLM-powered applications.
• Own the end-to-end engineering lifecycle, including architecture, build, deployment, and optimisation of AI services.
• Drive adoption of modern AI patterns, including RAG, agent orchestration, and event-driven workflows.
• Ensure production readiness through observability, resilience engineering, and cost optimisation.
• Oversee development of multi-agent systems using frameworks such as Semantic Kernel and AI Foundry.
• Implement deterministic orchestration patterns, context management, and memory strategies.
• Drive innovation in AI workflows, including voice AI, real-time inference, and autonomous decisioning systems.
• Ensure explainability and auditability across agent interactions.
• Embed secure-by-design principles across all AI workloads, including prompt injection defence and data protection.
• Partner with AI Safety and Compliance teams to enforce standards aligned to OWASP GenAI, NIST AI RMF, and ISO/IEC 42001.
• Implement guardrails for model usage, data handling, and fairness/bias mitigation.
• Ensure full audit trails and traceability of AI decisions.
• Lead engineering across Azure-native services, including Azure OpenAI, AKS, API Management, CosmosDB, and Service Bus.
• Ensure scalable, containerised deployments using Kubernetes with strong isolation and security practices.
• Drive infrastructure-as-code adoption using Bicep/Terraform and CI/CD automation pipelines.
• Optimise performance, latency, and cost efficiency across AI workloads.
• Build, lead, and scale high-performing AI engineering teams.
• Provide technical mentorship, career development, and engineering standards.
• Establish a strong engineering culture focused on quality, accountability, and continuous improvement.
• Act as a senior escalation point for complex technical challenges.
• Translate business problems into AI-driven solutions aligned to our organisational strategy.
• Collaborate with product, data, and leadership teams to prioritise and deliver high-impact initiatives.
• Contribute to the AI roadmap, investment planning, and capability maturity.
• Communicate progress, risks, and outcomes to senior stakeholders.

Technologies:

• Agentic AI
• AI
• API
• Architect
• Azure
• CI/CD
• Cloud
• Support
• Kubernetes
• LLM
• OWASP
• PowerShell
• Python
• RAG
• REST
• Redis
• SQL
• Security
• Terraform
• microservices

More:

We are hiring an AI Engineering Manager for our London or Glasgow team, focused on AI Platform Engineering & Delivery. This role is centred on designing and delivering our agentic AI strategy across Azure, with an emphasis on scalable, secure, and production-ready AI systems. We work with modern AI patterns, multi-agent orchestration, LLM-powered applications, and Azure-native services in a fast-paced, innovation-led environment. We value responsible AI, strong engineering standards, and collaborative leadership. We also provide important guidance on job fraud and advise candidates to verify any vacancy or contact person using our official website contact details.

last updated 36 week of 2026