Intelligent Automation Engineering Manager

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

1. Drive the delivery of AI enablement capabilities that support the adoption of Generative AI and agentic workflows across the organisation.
2. Own the roadmap, strategy, and engineering delivery of the MCP ecosystem, enabling secure integration between AI assistants, enterprise systems, data sources, and business applications.
3. Lead the design, development, deployment, and operational support of AI agents and AI-powered solutions.
4. Establish engineering standards and best practices for AI architecture, orchestration, retrieval, tool invocation, observability, governance, privacy, security, and cost management.
5. Review technical designs and architecture documentation to ensure solutions align with engineering, security, and governance standards.
6. Translate emerging AI opportunities into pragmatic delivery plans balancing innovation, scalability, reliability, and business outcomes.
7. Collaborate with integration, automation, platform, and cloud teams to ensure AI solutions integrate effectively with existing enterprise systems and workflows.
8. Partner with Product, Architecture, Security, Compliance, and Business stakeholders to ensure successful delivery and adoption of AI solutions.
9. Support Azure architecture decisions and work closely with CloudOps and InfoSec teams to ensure secure and scalable platform delivery.
10. Manage delivery planning, risks, dependencies, and stakeholder communications at both operational and executive levels.
11. Promote agile delivery methodologies, engineering best practices, reusable frameworks, and automation across the AI Enablement function.

1. Proven experience leading and developing high-performing Software Engineering, Platform Engineering, Automation, or AI Engineering teams.
2. Strong people leadership experience, including coaching, mentoring, performance management, and career development.
3. Experience delivering enterprise software platforms, developer tools, automation solutions, or AI-enabled products in production environments.
4. Strong understanding of Generative AI concepts, including: + AI Agents + LLMs + Prompt Engineering + Context Engineering + Tool/Function Calling + Retrieval-Augmented Generation (RAG) + Responsible AI practices
5. Experience leading discussions around system architecture, APIs, integrations, event-driven systems, security, scalability, and operational resilience.
6. Strong stakeholder management skills with the ability to influence Product, Architecture, Security, Compliance, and Business teams.
7. Excellent communication and presentation skills across both technical and non-technical audiences.
8. Experience delivering solutions within Agile software development environments.
9. Passion for building practical and scalable AI solutions that drive measurable business outcomes.

Desirable Experience

1. Experience building or operating AI Agents, AI Assistants, Copilots, or AI Enablement Platforms.
2. Experience with MCP (Model Context Protocol), MCP Servers, MCP Clients, or enterprise AI integration frameworks.
3. Knowledge of LLMOps, AI evaluation frameworks, model routing, and AI observability tooling.
4. Experience with enterprise integration technologies including APIs, Middleware, ESB, or iPaaS platforms.
5. Hands-on experience integrating internal and third-party systems.
6. Azure cloud experience, including: + Azure OpenAI + Azure AI Foundry + Azure App Services + Azure Functions + Azure Kubernetes Service (AKS) + Azure API Management + Azure Networking & Security
7. Experience with GitLab CI/CD or similar DevOps tooling.
8. Experience with Splunk or other observability platforms.
9. Previous software engineering or development background.
10. Experience within Financial Services, FinTech, Payments, or highly regulated environments.
11. Exposure to governance, privacy, risk, and security frameworks supporting enterprise AI adoption.

Delta Capita Group (a member of the Prytek Group) is a global managed services, consulting, and solutions provider with a unique combination of experience in Financial Services and technology innovation capability. Our mission is to reinvent the financial services value chain providing technology based mutualized services for financial institutions for non-differentiating services.