Project Manager (Data & AI)

Role overviewWe are hiring a Project Manager to lead Data and AI delivery for government and enterprise clients, from requirements through go-live and handover. The role needs an engineer who can read an architecture diagram, challenge a design, and then sit across the table from a client and keep the programme on track.Key responsibilitiesThe Project Manager owns scope, schedule, budget, quality and client confidence for each Data and AI engagement.Delivery and programme managementPlan and run Data and AI projects end to end: discovery, data readiness, model development, integration, testing, deployment and handover.Maintain the plan, RAID log, dependency map and change control, and report progress, risks and decisions needed to the steering committee on a fixed cadence.Manage vendors, third-party suppliers and subcontractors against agreed scope, milestones and service levels.Data and AI deliveryTurn business and legal requirements into a clear backlog covering data sources, pipelines, models, integrations and reporting.Work with architects and engineers on data quality, lineage, migration from legacy systems, and model validation, monitoring and retraining.Set acceptance criteria for AI features, including accuracy thresholds, human review steps and fallback behaviour when a model is wrong or unavailable.Flag the production risks of newer AI technologies, such as model drift, hallucination, vendor lock-in and immature tooling, and agree mitigations with the client before build.Client interfaceBe the day-to-day and executive point of contact for client sponsors, project directors and IT teams.Run workshops, requirement sessions, demos and steering meetings, and explain technical trade-offs in plain language to non-technical stakeholders.Manage expectations and negotiate scope, priorities and timelines with government stakeholders who may run legacy platforms such as AS/400 and follow established approval processes.Handle escalations early, and keep a written record of decisions, approvals and change requests.Security, governance and complianceMake security a delivery gate, not a final check: threat modelling, access control, encryption, secrets management and secure coding reviews are planned into every release.Make sure penetration tests, vulnerability remediation and data protection requirements, including data residency, are completed before go-live.Where no secure option exists for a requirement, document the residual risk and obtain a written client decision.Apply audit-ready documentation standards across requirements, design, test evidence and release approvals.Team leadershipDirect a cross-functional team of engineers, analysts, testers and designers, and resolve blockers quickly.Coach the team on agile delivery, estimation and release discipline.Required qualificationsCandidates must meet all of the following.Bachelor's degree in engineering (computer, software, electronics, data or a related discipline). A master's degree is an advantage.8 or more years in IT delivery, including at least 4 years managing projects or programmes with Data, Analytics or AI components.Hands-on understanding of data platforms and AI delivery: data pipelines and ETL, data warehouses or lakehouses, BI and reporting, machine learning lifecycle, and the basics of generative AI and its limits.Proven record of delivering systems in production for external clients, with direct ownership of budget, schedule and outcome.Strong client-facing ability: running steering committees, presenting to senior stakeholders, handling difficult negotiations and managing change requests.Working knowledge of Agile and Waterfall delivery, and of formal change, risk and release management.Working knowledge of information security practices, including secure SDLC, access control, data protection and audit requirements.Excellent written and spoken English. Arabic is a strong advantage.Willingness to travel to client sites in the GCC as the project requires.Professional certification is expected: PMP, PRINCE2 or equivalent.Preferred qualifications and competenciesExperience with government, justice, public-sector or regulated clients, including migration away from legacy platforms such as AS/400.Experience with cloud platforms (Azure, AWS or Google Cloud) and tools such as Azure DevOps or Jira.Exposure to Microsoft Azure AI, Power BI, Databricks, Python-based ML stacks or equivalent.Certifications such as PMI-ACP, Azure AI or Data Engineer, CISSP or CISM awareness, or ITIL.Experience with multilingual (Arabic and English) systems and right-to-left interfaces.How success is measuredMilestones delivered on the agreed dates and within approved budget.Client satisfaction, tracked through steering committee feedback and formal sign-offs.Zero critical or high security findings open at go-live.AI components meeting agreed accuracy and performance thresholds in production.Change requests, risks and decisions fully logged and traceable.What we offerLead role on large-scale digital transformation programmes for government clients in the GCC.Direct work with senior architects and executives.Competitive package, to be confirmed by HR, with professional certification and training support.