Senior Manager, AI Technical Program Manager

About Us

Headquartered in Singapore, SATS Ltd. is one of the world's largest providers of air cargo handling services and Asia's leading airline caterer. SATS Gateway Services provides airfreight and ground handling services including passenger services, ramp and baggage handling, aviation security services, aircraft cleaning and aviation laundry. SATS Food Solutions serves airlines and institutions, and operates central kitchens with large-scale food production and distribution capabilities for a wide range of cuisines.

SATS is present in the Asia-Pacific, the Americas, Europe, the Middle East and Africa, powering an interconnected world of trade, travel and taste. Following the acquisition of Worldwide Flight Services (WFS) in 2023, the combined SATS and WFS network operates over 225 stations in 27 countries. These cover trade routes responsible for more than 50% of global air cargo volume. SATS has been listed on the Singapore Exchange since May 2000. For more information, please visit www.sats.com.sg

Why Join Us

At SATS, people are our greatest asset and we build our success on the knowledge, expertise and performance of every contributor, by embracing diversity and uniqueness. As part of our holistic approach and commitment to embracing FAM (Fulfilling, Appreciated, Meaningful) in the workplace, we offer the runway to develop Fulfilling careers that foster your career growth, recognising and Appreciating the strength of talent and capabilities that we continue to build internally; and inspiring and encouraging each other to make Meaningful contributions in the work we do at SATS.

Key Responsibilities

The Role

The Senior Manager, Technical Program Management is a responsible for driving the successful delivery of a growing portfolio of AI, Data Engineering, and Data Science initiatives. Partnering closely with the Head of AI and cross-functional stakeholders, the incumbent will translate organisational strategy into a structured, prioritised, and well-governed portfolio of programmes across Generative AI, Computer Vision, Optimisation, Digitalisation, Data Engineering, and Data Science. While not directly involved in software development, the successful candidate must bring strong technical acumen, exceptional stakeholder management skills, and a proven track record of leading complex technology programmes at scale.

Key Responsibilities

Portfolio & Delivery Leadership

• Own end-to-end planning, prioritisation, and tracking for the AI/ML, GenAI, CV, Optimization, Digitalization, Data Engineering, and Data Science portfolio - scope, milestones, resourcing, and critical path.
• Build and maintain the master roadmap across AI COE, Data Engineering, and Data Science workstreams; run the intake and prioritisation process against capacity and business value.
• Identify cross-team dependencies and blockers early and drive them to resolution.
• Own the hiring/onboarding plan for the AI COE build-out, and for Data Engineering/Data Science roles where TPM coverage extends to, in partnership with HR

Cross-Functional Coordination

• Coordinate between the AI COE, Data Engineering, and Data Science leads to align on sequencing and shared infrastructure/data needs (e.g. dependencies between data system integration, enterprise MDM, semantic layer, pipeline, etc.)
• Set the planning cadence (quarterly planning, sprint/iteration planning, roadmap reviews, retrospectives) suited to a mixed research/engineering/data team and ensuring consistency across teams.

Executive Stakeholder, Budget & Vendor Management

• Act as the senior point of contact for business-unit and business stakeholders on AI and data program status, timelines, priorities, and trade-offs
• Support the Head of AI in building business cases and investment proposals; own program budget tracking, forecasting, and variance reporting
• Lead vendor and external partner strategy and engagements (cloud providers, specialist agencies, tooling vendors) where they intersect with program delivery, including commercial and performance reviews

Governance, Risk & Reporting

• Establish and run program governance: stage gates, risk and issue management, change control, and dependency tracking appropriate to a research/engineering/data environment
• Own steering-committee and senior leadership reporting - portfolio status, budget/headcount tracking against the hiring plan, delivery health, and key decisions required
• Ensure programs meet relevant compliance, data governance, and Fair Consideration Framework/work-pass requirements in coordination with HR/legal

Team & Practice Building

• Define and continuously improve the program management playbook, templates, and tooling for the team
• Coach and mentor engineers and leads on planning, estimation, and delivery practices; as the portfolio grows, recruit and lead additional TPMs/PMs

Technical Fluency

• Maintain strong understanding of the underlying architecture (ML/GenAI pipelines, data system integration, enterprise MDM, semantic layer, etc.) to ask the right questions, sanity-check estimates, and assess technical risk - without being expected to write production code
• Partner with the Lead AI/Platform Engineer and Data Engineering/Data Science leads to keep the technical roadmap and program plan in sync across functions

Key Requirements

• Bachelor's or Master's degree in a technical field (Computer Science, Engineering, Information Systems) or equivalent experience.
• 12+ years of program/project management experience, including 5+ years leading complex, multi-team technical programs or a portfolio of programs - ideally spanning AI/ML, data engineering/data platform, or software engineering organizations.
• Experience owning program budgets and building business cases or investment proposals.
• Strong working technical fluency: able to read an architecture diagram, understand cloud/infra and ML/GenAI concepts well enough to evaluate risk and effort, and hold engineers accountable to estimates.
• Experience managing hiring pipelines, budgets, or headcount plans alongside HR/Talent Acquisition.
• Experience establishing or improving program governance and delivery standards for a team or function.
• Project/program management certification preferred (PMP, PgMP, or Agile/Scrum equivalent).
• Experience standing up or scaling an AI/ML Centre of Excellence or platform team from an early stage.
• Prior program management experience spanning both AI/ML and data engineering/data science functions, with a view of how data system integration, enterprise MDM, semantic layer, data pipelines, and ontology design feed downstream models and analytics.