Technical Program Manager

Overview

Requirements

• 10+ years of technical project and program delivery, with a track record of owning complex, multi-workstream engagements.
• Demonstrable experience delivering GenAI, data, and advanced analytics solutions - hands-on familiarity with the technology is essential, not just theoretical exposure.[AY1.1]
• Experience spanning the full engagement lifecycle: RFP response, project delivery, and post-go-live managed services.
• Proven client-facing experience at senior and executive level - regional stakeholder management is a significant advantage.
• Experience operating in large enterprise or government delivery environments, particularly in sectors such as Energy, Oil & Gas, or Public Sector.
• Background in multi-vendor delivery environments with complex dependencies and distributed teams.
• Key Duties & Responsibilities (List key responsibilities of the job)
• Program Leadership — End to End
• Own the full delivery lifecycle: from RFP response and solutioning through to go-live and post-delivery managed services.
• Define scope, roadmaps, delivery plans, milestones, and governance frameworks from day one of engagement.
• Drive sprint and release planning across distributed engineering, data, and AI teams in Agile and hybrid delivery models.
• Manage risks, dependencies, budgets, and timelines with rigor - always maintaining meticulous documentation and program controls.
• Establish and embed PMO practices, reporting cadences, and delivery metrics across the program you own.

Client Advisory & Stakeholder Management

• Act as a trusted advisor to client leadership - translating complex technical delivery into clear, confident, executive-level communication.
• Build and sustain strong relationships with senior client and government stakeholders across the UAE and wider Middle East region.
• Lead board-level reporting and steering committee engagement, presenting progress, risks, and strategic recommendations with authority.
• Navigate multi-vendor and multi-stakeholder environments, aligning competing priorities and maintaining momentum.

RFP & Pre-Sales Contribution

• Play a hands-on role in developing RFP responses and solution proposals - not simply reviewing, but actively writing, structuring, and shaping bids.
• Work with architecture and technical teams to estimate scope, effort, and delivery approaches for complex AI, data, and platform programs.
• Contribute to solution workshops and technical discussions, bringing delivery credibility to pre-sales engagements.

AI & Data Delivery

• Lead delivery of AI and machine learning solutions, data engineering pipelines, analytics platforms, and cloud infrastructure programs.
• Coordinate effectively with data scientists, ML engineers, and platform teams - you do not need to code, but you need to understand deeply.
• Manage delivery across cloud-native (Azure, AWS, GCP) and on-prem environments, microservices architectures, API ecosystems, and CI/CD pipelines.

• Team Leadership & Mentoring

• Serve as a mentor and coach to internal delivery teams - instilling best practices, building capability, and raising standards across the organization.
• Coordinate international vendors and distributed teams, ensuring alignment and accountability without direct line authority.
• Foster a culture of continuous improvement, learning, and delivery excellence within your programs.
• Key Skills (Core skills and key words that will be used by workable AI for the job or role). You do not need to be an engineer, but you must be able to hold your own in a technical conversation. We expect strong familiarity with:
• AI and ML solution delivery - understanding of model development lifecycles, data pipelines, RAG, and agentic AI application architectures. You are in touch with what is happening in the rapidly evolving AI ecosystem.
• Cloud-native platforms: Azure, AWS, or GCP — including microservices, containerization, and distributed system design.
• Data platforms: data lakes, data warehouses, analytics ecosystems, and data engineering pipelines.
• APIs, system integration, and enterprise application architectures.
• DevOps, CI/CD practices, and modern SDLC methodologies.
• Agile / Scrum / SAFe and hybrid delivery frameworks; Jira and equivalent tooling.