Intelligent Automation Engineering Manager

Role - Intelligent Automation Engineering Manager

Employment Type - Fixed term contract - 6 months

Mode - Hybrid/ Remote

Role Overview:

We are seeking an Intelligent Automation Engineering Manager to lead a high-performing AI Enablement engineering team focused on accelerating the responsible adoption of AI across the enterprise. The successful candidate will drive the delivery of enterprise-grade AI agents, AI enablement platforms, and integration capabilities, while providing technical leadership, people management, and strategic direction across a rapidly evolving AI ecosystem.

This role will partner closely with Product, Architecture, Security, Compliance, CloudOps, and Integration teams to ensure AI solutions are secure, scalable, well-governed, and deliver measurable business value.

Key Responsibilities:

1. Lead, mentor, and develop a team of engineers, fostering a culture of technical excellence, innovation, and continuous improvement.

2. Drive the delivery of AI enablement capabilities that support the adoption of Generative AI and agentic workflows across the organisation.

3. Own the roadmap, strategy, and engineering delivery of the MCP ecosystem, enabling secure integration between AI assistants, enterprise systems, data sources, and business applications.

4. Lead the design, development, deployment, and operational support of AI agents and AI-powered solutions.

5. Establish engineering standards and best practices for AI architecture, orchestration, retrieval, tool invocation, observability, governance, privacy, security, and cost management.

6. Review technical designs and architecture documentation to ensure solutions align with engineering, security, and governance standards.

7. Translate emerging AI opportunities into pragmatic delivery plans balancing innovation, scalability, reliability, and business outcomes.

8. Collaborate with integration, automation, platform, and cloud teams to ensure AI solutions integrate effectively with existing enterprise systems and workflows.

9. Partner with Product, Architecture, Security, Compliance, and Business stakeholders to ensure successful delivery and adoption of AI solutions.

10. Support Azure architecture decisions and work closely with CloudOps and InfoSec teams to ensure secure and scalable platform delivery.

11. Manage delivery planning, risks, dependencies, and stakeholder communications at both operational and executive levels.

12. Promote agile delivery methodologies, engineering best practices, reusable frameworks, and automation across the AI Enablement function.