CAF Ecosystem and Operations Manager

The Cognitive Automation Factory Ecosystem and Operations Lead is a senior leadership role responsible for the end‑to‑end operational performance, ecosystem management, and strategic evolution of the Group’s Cognitive Automation Factory. The role serves as the operational backbone and successor‑level counterpart to the Head of Cognitive Automation, ensuring the CAF operates as a high‑performance, multi‑technology, multi‑partner industrial engine that delivers significant business benefits through applied AI and automation.

Responsibilities

• Factory Leadership & Operational Excellence: Lead the operational performance of the CAF across the Group. Industrialise AI and automation delivery through standardised engineering practices, governance, quality controls and reusable frameworks. Ensure predictable, high‑quality delivery across multiple concurrent programmes and products. Own delivery economics, capacity planning, utilisation, and multi‑shore optimisation.
• Business Value & Benefits Realisation: Ensure all AI and automation initiatives are anchored in measurable business value. Track and govern realised versus forecast benefits (cost‑out, productivity, error reduction, revenue enablement). Act as a senior escalation point for under‑performing initiatives. Partner with Finance and operating‑company stakeholders to validate tangible benefits delivered.
• Ecosystem & Partner Management: Lead and optimise a blended ecosystem of strategic partners and internal engineering squads. Manage commercial performance, contractual KPIs, and delivery standards. Ensure knowledge transfer and capability uplift within the internal team. Maintain a competitive, scalable, and innovation‑led partner model.
• Technology & Architecture Governance: Provide senior oversight across the automation and AI technology stack, including RPA platforms (e.g., UiPath, Power Automate), AWS‑based cloud‑native architectures, agentic AI frameworks (Agent Core, LangChain, LangGraph), large language models, orchestration frameworks and event‑driven architectures, Document AI, evaluation frameworks, and observability, monitoring and guardrails for AI agents. Ensure scalable, secure, compliant, and production‑grade solutions. Champion best practices in AI governance, risk management, and model lifecycle management.
• Senior Stakeholder Engagement: Engage senior leaders across operating companies at Director and C‑level. Translate AI and automation capabilities into business language. Influence prioritisation decisions and roadmap alignment across the Group. Represent the CAF in senior governance forums.
• Talent & Capability Development: Build and mentor high‑performing automation and AI delivery leaders. Establish clear career paths and succession planning within the CAF. Foster a culture of engineering excellence, accountability, and measurable impact. Drive continuous capability uplift across RPA, AI, and agentic systems.

Qualifications

Essential Experience: 12+ years of enterprise technology delivery experience, with at least 7+ years leading large‑scale automation or AI programmes. Proven track record of delivering significant, tangible business benefits through applied AI and automation. Experience managing multi‑disciplinary teams combining internal staff and strategic delivery partners. Experience operating at senior stakeholder level (Director/C‑level engagement). Strong commercial acumen, including budget ownership and benefits tracking.

Technical Depth (Non‑Hands‑On but Credible): RPA platforms such as UiPath and Power Automate. Cloud‑native architectures (preferably AWS). Agentic AI frameworks (LangChain, LangGraph, agent orchestration). Multi‑LLM strategies and model selection. EVAL frameworks for LLM/agent performance. Observability, logging, guardrails and governance for AI agents. Workflow orchestration and integration patterns. Enterprise‑grade security and compliance considerations for AI systems.

Desirable Experience: Experience within aviation, transportation, logistics, or other complex operational industries. Experience scaling an AI or automation factory model. Exposure to regulated environments. Knowledge of EU AI Act and enterprise AI governance frameworks.

Personal Attributes: Strategic thinker with strong operational discipline. Calm under pressure in complex, multi‑stakeholder environments. Commercially sharp, data‑driven, and outcome‑oriented. High credibility with both engineers and executives. Not dazzled by hype; focused on value.

Benefits: Challenging career in a dynamic industry with a multi‑cultural environment. Work‑life balance support and a range of benefits including health insurance, pension, and performance bonuses. We are an equal opportunities employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.