AI Finance Program Lead

SGS; Makati; Hybrid; PHP 1,100,000 - 1,800,000; Full time

Benefits offered by this job

Flexible schedule

Hybrid work model

SGS University learning opportunities

Multinational collaboration

Job summary

SGS is seeking an AI Finance Program Lead to shape and execute the enterprise AI agenda for Finance. You will drive strategy, governance, and a portfolio of scalable AI solutions across Finance Operations, IT, Data, Risk and business teams.

The role focuses on value realization, responsible AI, privacy and regulatory compliance while delivering measurable productivity and decision improvements. You will lead multidisciplinary teams, establish program governance, manage budgets and delivery

Qualifications

• 10+ years in Finance transformation, AI or digital programs
• Experience leading cross-functional programs from strategy to production deployment
• Strong understanding of Finance operations and end-to-end processes
• Experience with responsible AI, data privacy, security, risk and controls

Responsibilities

• Translate Finance strategy into a multi-year AI roadmap and investment plan
• Own the Finance AI opportunity funnel from ideation to sequencing and governance
• Lead cross-functional delivery from discovery to production deployment and scale
• Embed responsible AI, data governance and controls across the lifecycle
• Build adoption plans and a Finance AI community for knowledge sharing
• Set and monitor value realization, benefits, and performance metrics
• Lead multidisciplinary teams and external partners with clear outcomes

Skills

Enterprise AI strategy

Portfolio governance

Cross-functional leadership

Stakeholder influence

Change management

Education

Bachelor's or Master's degree in finance, business, technology, data, engineering or related field

Job description

SGS is the world’s leading Testing, Inspection and Certification company. We operate a network of over 2,500 laboratories and business facilities across 115 countries, supported by a team of over 100,000 dedicated professionals. With more than 145 years of service excellence, we combine the precision and accuracy that define Swiss companies to help organizations achieve the highest standards of quality, compliance and sustainability.

Our brand promise – “when you need to be sure” – underscores our commitment to trust, integrity and reliability, enabling businesses to thrive with confidence. We proudly deliver our expert services through the SGS name and a portfolio of trusted specialized brands, including Applied Technical Services, Brightsight, Bluesign and Nutrasource.

Job Description

The AI Finance Program Lead is responsible for shaping and executing the enterprise AI agenda for Finance, turning business priorities into a governed portfolio of scalable AI solutions. The role leads the full lifecycle from opportunity discovery and use-case prioritization through design, delivery, adoption and value realization. Working across Global and local Finance Operations, IT, Data, Risk and business teams, the role ensures that AI solutions improve productivity, decision quality, controls, customer experience and employee experience while meeting responsible AI, data privacy, security and regulatory requirements.

Key responsibilities encompass, but are not limited to:

1. AI Strategy and Roadmap

• Translate Finance strategy and pain points into a multi-year AI vision, roadmap and investment plan aligned with enterprise technology and data strategies.
• Identify where predictive AI, generative AI, intelligent agents, machine learning and advanced analytics can create material business value.
• Define target outcomes, success measures and operating principles for AI-enabled Finance.
• Track relevant market and technology developments and convert them into practical opportunities for Finance.

2. Use-Case Portfolio and Governance

• Own the Finance AI opportunity funnel, including ideation, assessment, prioritization, sequencing and stage-gate decisions.
• Evaluate use cases against strategic fit, value potential, feasibility, data readiness, control impact, scalability and change effort.
• Maintain a transparent portfolio view covering scope, ownership, milestones, investment, dependencies, risks, benefits and decisions.
• Prepare recommendations for governance forums on initiating, accelerating, reshaping, scaling, pausing or stopping initiatives.
• Operate within the framework of Finance Projects Portfolio Management

3. Program Delivery and Solution Industrialization

• Lead cross-functional delivery from discovery and proof of value through minimum viable product, production deployment and scale.
• Establish clear program governance, workstreams, decision rights, delivery plans, budgets, quality standards and escalation paths.
• Coordinate Finance subject-matter experts, product owners, data scientists, engineers, architects, vendors and implementation partners.
• Ensure solutions are supportable, monitored and integrated into business processes, controls and the target technology landscape.

4. Responsible AI, Data and Controls

• Embed responsible AI requirements throughout the lifecycle, including human oversight, transparency, explainability, fairness and appropriate use.
• Partner with Data, IT, Cybersecurity, Privacy, Legal, Compliance, Internal Control and Audit to meet enterprise policies and regulatory obligations.
• Ensure robust data ownership, quality, lineage, access, retention and model or agent monitoring are built into each solution.
• Maintain auditable documentation, risk assessments, approvals and controls proportionate to the use case.

5. Adoption, Capability and Change

• Build adoption plans with Finance leaders, Change Management and Learning teams, ensuring new AI-enabled ways of working are understood and embedded.
• Create a Finance AI community and practitioner network to share knowledge, reusable assets, lessons learned and responsible experimentation practices.
• Strengthen AI literacy among Finance leaders and employees through targeted learning, practical guidance and coaching.
• Monitor user experience, adoption and behavioural change; address barriers and refine solutions based on feedback.

6. Value Realization and Performance

• Set business-case, baseline and benefit-tracking standards for the Finance AI portfolio.
• Ensure financial and non-financial benefits are measurable, attributable, validated and sustained after implementation.
• Report delivery confidence, adoption, productivity, quality, customer, risk and financial outcomes to senior stakeholders.
• Challenge assumptions and intervene early where delivery, adoption, control or value outcomes are at risk.

7. Stakeholder and Team Leadership

• Act as a trusted advisor to Finance executives and governance bodies on AI opportunities, choices, trade-offs and risks.
• Influence across a global matrix and align Global Process Owners, Finance Operations, regions, countries and enabling functions around common priorities.
• Lead multidisciplinary teams and external partners through clear outcomes, empowerment, disciplined execution and constructive challenge.
• Foster a culture of curiosity, experimentation, accountability and value-focused innovation.

Qualifications

• 10+ years of progressive experience in Finance transformation, AI or digital programs, technology-enabled change, product management or management consulting.
• Proven track record of leading complex, cross-functional programs from strategy and business case through production deployment, adoption and value realization.
• Strong understanding of Finance operations and end-to-end processes; experience in a shared services / GBS or global matrix environment is preferred.
• Practical understanding of generative AI, machine learning, intelligent agents, automation, analytics and the data foundations required to scale them.
• Demonstrated experience applying responsible AI, data privacy, security, risk and control principles in an enterprise setting.
• Strong commercial acumen with the ability to quantify value, manage investment and make evidence-based portfolio decisions.
• Bachelor's or Master's degree in finance, business, technology, data, engineering or a related field; relevant AI, project, product or change certification is an advantage.

Skills

• Enterprise AI strategy and roadmap development
• AI use-case discovery, assessment and portfolio prioritization
• Program, product and project management across agile and traditional delivery models
• Generative AI, machine learning, intelligent agents, automation and advanced analytics
• Finance process knowledge and business process redesign
• Responsible AI, model risk, privacy, security and internal controls
• Data governance, quality, lineage and readiness
• Business-case development, benefits management and value realization
• Change management, adoption and capability building
• Vendor, partner, budget and commercial management
• Executive communication, facilitation and senior stakeholder influence
• Cross-functional team leadership in a global matrix
• Ability to move confidently between strategic perspective and technical or operational detail
• High judgment, curiosity, learning agility and comfort with ambiguity

Additional Information

Ability and willingness to travel up to 20%, depending on program needs. The role operates globally and requires flexibility to collaborate across time zones. The role may lead dedicated and matrixed program resources, product teams, subject-matter experts and external partners.

Why SGS?

• Join a globally recognized and stable company, a leader in the Testing, Inspection, and Certification (TIC) industry.
• Enjoy a flexible schedule and a hybrid work model.
• Access continuous learning opportunities through SGS University and Campus.
• Collaborate in a multinational environment with colleagues from various continents.