cfgi - Data & AI - Technical Project Manager

• 6+ years of experience in technology delivery, with at least 3 years leading client-facing data, analytics, artificial-intelligence or software-engineering projects. • What sets you apart: • Hands-on experience leading engineering teams of three or more, including distributed teams and teams combining internal, vendor or partner engineers. • Practical experience running Scrum and Kanban teams and selecting agile, waterfall or hybrid delivery approaches to suit client needs. • Experience translating statements of work into delivery plans, backlogs, milestones, acceptance criteria and governance routines. • Experience managing fixed-fee and time-and-materials budgets, forecasts, change requests, subcontractor delivery and engagement economics. • Technical fluency across data platforms and pipelines, APIs, system integration, cloud environments and continuous integration and delivery. • Understanding of AI delivery, including retrieval-augmented generation, agents, model evaluation, machine-learning operations, data readiness and production monitoring. • Experience working with software development lifecycle practices, testing, change management, security reviews and release governance. • Experience communicating with clients and executives, including chairing steering committees and explaining technical status, risks and trade-offs in business terms. • Working awareness of data-protection obligations, including Singapore’s Personal Data Protection Act and relevant laws in other client jurisdictions. • Experience applying practical AI governance, including relevant Singapore Model AI Governance Frameworks, alongside applicable law and client policy. • Experience with delivery tools such as Jira, Azure DevOps or Confluence. • Relevant agile or project-management certifications, such as Professional Scrum Master, Certified ScrumMaster, PMI Agile Certified Practitioner, SAFe Scrum Master, Project Management Professional (PMP) or PRINCE2 Practitioner. • Familiarity with delivery and governance approaches such as the V-model, PRINCE2, the PMI PMBOK Guide, SAFe and DevOps practices. • Understanding of data and lakehouse platforms such as Databricks, Snowflake or Microsoft Fabric, and cloud platforms such as AWS, Microsoft Azure or Google Cloud. • Healthcare and life-sciences delivery experience, including GxP environments, computerised system validation, or clinical and commercial data projects. • Experience delivering finance-function or enterprise-resource-planning programmes. • Knowledge of cyber security and IT governance frameworks such as ISO/IEC 27001, the NIST Cybersecurity Framework or COBIT. • Experience with IT general controls and finance controls, including access, change management, IT operations, approvals, reconciliations and segregation of duties; SOX Section 404 experience is also useful. • Experience transitioning solutions into managed services, including service-level design and IT service-management practices such as ITIL. • A delivery leader who stays close to engineering and can challenge estimates, read architectures and assess technical trade-offs with architects. • Someone who is comfortable managing uncertainty in AI projects through time-boxed experiments, evaluation-based acceptance criteria and early data-readiness checks. • A clear, pragmatic communicator who builds trust with clients, engineers, partners and executive sponsors. • A structured problem-solver who balances delivery quality, commercial discipline, security, privacy and client outcomes.