Data & AI - Technical Project Manager

Data & AI – Technical Project Manager

CFGI, founded in 2000, is a dynamic and fast-growing financial consulting firm, serving as the trusted partner to CFOs and their organizations. We help clients tackle complex challenges across accounting, financial reporting, transactions, regulatory compliance, digital transformation, data analytics, and artificial intelligence. We blend deep technical expertise with a hands-on, entrepreneurial approach to help the world’s leading companies move forward with confidence.

CFGI is expanding its Data & AI practice across Asia-Pacific and is seeking a Technical Project Manager to lead client delivery. You run data-engineering, artificial-intelligence-engineering and strategy engagements from contract
signature to client acceptance, and engineering work through to production handover. You lead a team of
engineers, run delivery on agile principles and act as the client's day-to-day point of contact.

You will deliver client data and artificial-intelligence engagements on time, on budget and to the agreed scope. Our
engagements run end to end and across the full stack. They span data strategy and architecture, data
platforms and pipelines, agentic and generative-artificial-intelligence solutions, and the operation of those
solutions in production. You turn the signed statement of work into a plan and a backlog, and you lead the
team that delivers it.

This is a technical role, not just a coordination role, so deep engineering experience is required to challenge an estimate, read an architecture and judge a technical trade-off with the architect. Artificial-intelligence work can add
uncertainty from data, evaluation and model behaviour. You plan for that with time-boxed experiments,
acceptance criteria based on evaluation results, and early checks on whether the client's data is ready.

What you might expect

Mobilise each engagement. You convert the proposal and statement of work into a release plan, a prioritised backlog, milestones, acceptance criteria, a responsibility matrix and a governance cadence agreed with the client.

Run agile delivery. You facilitate Scrum events where Scrum is used, and you manage workflow, work-in-progress limits and flow measures where Kanban is used. Where a client needs fixed-fee milestones or formal stage gates, you adapt governance to those contractual and regulatory requirements.

Lead the delivery team. You agree capacity and commitments with the engineers, remove blockers and set working norms for teams of typically three to ten engineers. The team often spans CFGI engineers and partner engineers in several Asia-Pacific time zones. You coach junior team members, while the engineers' line management stays with the partner.
Own the client relationship day to day. You prepare and chair steering committees, write clear status reports and manage expectations. You raise risks and decisions early, in business terms, so that sponsors can act before an issue affects the timeline.

Control scope, budget and commercials. You track effort against fixed-fee and time-and-materials budgets, forecast the cost at completion and protect the engagement margin. You include cloud, platform and model-consumption costs in the forecast. You also separate backlog refinement within the agreed scope from changes to contractual scope, fees or milestones, which need the client's signed approval before work starts.

Manage risks, dependencies and quality. You keep the risks, assumptions, issues and dependencies log current. Typical dependencies include client data access, environment provisioning and security approvals. Your definition of done covers testing, evaluation thresholds, documentation and the control evidence that regulated clients
require.

Steer artificial-intelligence delivery specifically. You agree stop, pivot and scale criteria with the sponsor before a proof of concept starts. A solution moves to production only when evaluation results meet the agreed threshold and the model-risk and data-privacy sign-offs are in place. You also design human review steps with the client's process owners.

Coordinate release readiness. With the architect and the client's owners, you confirm security and privacy review, monitoring, rollback and support ownership before each release. For agentic solutions, you agree the permitted actions, human approvals and escalation paths.

Plan validation in regulated work. In healthcare and life-sciences engagements where good-practice (GxP) rules apply, you plan validation and its evidence from the start. You also bring clinical, quality and safety owners into the design of acceptance tests.

Hand over to production and to run. You plan cut-over, hypercare and the transition to the client's team or to a CFGI managed service, with runbooks, service levels and support arrangements agreed in advance. The handover names who owns model performance in production, including the drift thresholds and the run-cost budget.

Build the practice's delivery playbook. You create reusable plans, templates and estimation baselines from each engagement. You also support the partner on proposals by preparing estimates, staffing plans and delivery approaches.

What you must have

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 engagemen