Technical Programme Manager (AI-SDLC) IRC303384

About the Role

Domain and Technical Expertise

• Demonstrate deep AI SDLC and LLMOps knowledge, including RAG, agentic frameworks, fine-tuning, prompt engineering, vector storage, and model observability.
• Bring expertise in enterprise DevOps or DevSecOps, CI/CD automation, trunk-based development, and AI coding assistants.
• Apply AI ethics, IP guardrails, security standards for AI-generated software, and emerging AI regulations.

Programme and Delivery Leadership

• Have 15+ years in digital/software engineering or IT consulting.
• Have led complex fixed-outcome programmes worth £10M+ annual revenue and distributed teams of 100+ people.
• Use DORA metrics, the SPACE framework, and productivity tracking for AI-augmented teams.
• Apply financial governance, P&L management, margin optimisation, and commercial risk mitigation.

Strategic Influence and Communication

• Act as a trusted executive advisor who connects business goals, technical execution, and engineering culture.
• Articulate AI adoption business cases and ROI through clear, metric-driven communication.
• A degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field is preferred.

Delivery and AI Engineering Oversight

• Drive full-lifecycle AI software programmes, including custom LLM solutions, RAG architectures, agentic workflows, and AI-powered SDLC tooling.
• Integrate AI tools into client pipelines to improve developer productivity and code quality.
• Review AI architecture for scalability, maintainability, and security.
• Lead AI platform engineering and software transformation pre-sales solutioning.
• Establish AI quality governance, automated evaluations, regression testing, and hallucination monitoring.

Governance and Financial Accountability

• Take financial responsibility for £10M+ annual-revenue engineering programmes and protect delivery margins.
• Mitigate model drift, IP leakage, licensing, privacy, and security risks.
• Ensure compliance with AI governance standards, copyright guidance, GDPR, and the EU AI Act.

Leadership and Stakeholder Management

• Direct distributed teams of software, AI/ML, prompt, DevOps/LLMOps, and QA specialists.
• Serve as the primary delivery escalation point for client engineering executives.
• Champion modern engineering standards, AI-driven development patterns, and prompt engineering best practices.

What We Offer

• Hybrid working options can flex according to business, customer, and individual needs.
• Benefits include health and wellness support, private healthcare, pension, training budget, recognition schemes, and an annual volunteering day.