Technical Project Manager, Data & AI

CFGI

. Lead client data-engineering, artificial-intelligence-engineering and strategy engagements from contract signature to client acceptance and production handover .

Posted 10/14/2026full-timeSingaporeMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data and artificial intelligence engineering projects, managing client relationships, and delivering on time and within budget. Proficient in agile methodologies, project governance, and compliance with regulatory requirements in healthcare and life sciences.

Highest-signal resume keywords

Data Engineering LeadershipArtificial Intelligence DeliveryAgile Project ManagementClient-Facing CommunicationBudget Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PlatformsAPIsSystem IntegrationCloud EnvironmentsContinuous IntegrationMachine Learning OperationsSoftware Development LifecycleChange ManagementTestingData Protection Compliance

Soft Skills

Team LeadershipCoachingClient ManagementFacilitationCommunication

Tools & Technologies

JiraAzure DevOpsConfluenceDatabricksSnowflakeMicrosoft FabricAWSMicrosoft AzureGoogle Cloud

Certifications & Qualifications

PSMCSMPMI-ACPSAFe Scrum MasterPMPPRINCE2 Practitioner

Industry Keywords

GxPHealthcareLife SciencesISO/IEC 27001NIST Cybersecurity FrameworkCOBITSOX Section 404ITIL

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityPMP

About the role

Key responsibilities & impact

Lead client data-engineering, artificial-intelligence-engineering and strategy engagements from contract signature to client acceptance and production handover
Deliver data and artificial-intelligence engagements on time, on budget and to agreed scope
Convert proposals and statements of work into release plans, prioritised backlogs, milestones, acceptance criteria, responsibility matrices and governance cadences
Facilitate Scrum events and manage Kanban workflow, work-in-progress limits and flow measures
Adapt governance for fixed-fee milestones, formal stage gates and contractual or regulatory requirements
Lead teams of typically three to ten engineers, remove blockers, agree capacity and commitments, and coach junior team members
Act as the client’s day-to-day point of contact; chair steering committees, prepare status reports and manage expectations
Track budgets, forecast cost at completion, protect engagement margins and manage scope changes and commercial approvals
Maintain risks, assumptions, issues and dependencies logs and ensure testing, evaluation thresholds, documentation and control evidence
Steer AI delivery through stop, pivot and scale criteria, evaluation-based acceptance, model-risk and data-privacy sign-offs, and human review design
Coordinate release readiness, including security and privacy reviews, monitoring, rollback and support ownership
Plan GxP validation and evidence for regulated healthcare and life-sciences engagements
Plan cut-over, hypercare and transition to the client or CFGI managed service with runbooks, service levels and support arrangements
Build reusable delivery plans, templates and estimation baselines and support proposals with estimates, staffing plans and delivery approaches

Requirements

What you’ll need

6+ years of experience in technology delivery
At least 3 years leading client-facing data, analytics, artificial-intelligence or software-engineering projects
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
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 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
Nice-to-have experience with Jira, Azure DevOps or Confluence
Nice-to-have relevant agile or project-management certifications, including PSM, CSM, PMI-ACP, SAFe Scrum Master, PMP or PRINCE2 Practitioner
Nice-to-have familiarity with V-model, PRINCE2, PMI PMBOK, SAFe and DevOps practices
Nice-to-have understanding of Databricks, Snowflake, Microsoft Fabric, AWS, Microsoft Azure or Google Cloud
Nice-to-have healthcare and life-sciences delivery experience, including GxP, computerised system validation, or clinical and commercial data projects
Nice-to-have experience delivering finance-function or enterprise-resource-planning programmes
Nice-to-have knowledge of ISO/IEC 27001, NIST Cybersecurity Framework or COBIT
Nice-to-have experience with IT general controls, finance controls and SOX Section 404
Nice-to-have experience transitioning solutions into managed services, including service-level design and ITIL practices

Benefits

Comp & perks

Exposure to the full commercial and delivery lifecycle
Client ownership and visibility with senior leadership
Opportunity to help shape the growth of the Data & AI practice across APAC
Continued progression opportunities within the firm