AI Finance Program Lead

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 behavioral 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.
• Bachelors or Masters 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.

Apply Now:
At SGS we are committed to fostering an open friendly and supportive culture that thrives on teamwork. We value diversity and provide endless opportunities to learn grow your expertise and fulfill your potential. Apply now to join our motivated and dynamic team!

Remote Work :

No

Employment Type :

Full-time