Head of AI Engineering, Commercial

FIS processes trillions of dollars in transactions annually for some of the world’s largest banks and financial institutions. That scale generates data assets that almost no other company on earth can match—and we’re just beginning to unlock them with AI. We’re hiring a Head of AI Engineering, Commercial to lead a high‑autonomy tiger team of Data Scientists and ML Engineers in London. You will architect and ship production AI systems—from intelligent agents to predictive analytics—that directly reshape how our global commercial organization sells, prices, and serves clients. This is not an advisory role. You will own the roadmap, build the team, and deliver.

What You Will Be Doing

• Own the AI/ML roadmap for FIS’s global commercial organization—translating strategic priorities into a sequenced delivery plan with measurable outcomes.
• Design, build, and deploy AI Agents at enterprise scale—automated lead‑generation agents, intelligent pricing systems, deal‑scoring models, and next‑generation agentic workflows.
• Develop advanced ML models and agentic systems addressing predictive analytics, optimization, personalization, and intelligent automation across fintech use cases.
• Architect the integration layer for how ~1,500 commercial team members interact with AI—including model governance, tooling, infrastructure, and MLOps frameworks.
• Lead and grow a high‑calibre team of Data Scientists, fostering a culture of rapid experimentation, technical excellence, and continuous learning.
• Drive innovation in Generative AI, Agentic AI, deep learning, and large‑scale ML deployment—staying ahead of the curve on foundational models, LLMs, and autonomous agents.
• Champion MLOps best practices, cloud‑native development (Azure preferred), and scalable production deployment pipelines.
• Collaborate cross‑functionally with Sales, Product, Engineering, and more to embed AI capabilities into workflows, products, and commercial strategies.
• Present AI program outcomes, strategic recommendations, and technical guidance to senior leadership and C‑suite audiences.

Why This Role

• We’re looking for builders who’ve shipped AI at scale inside world‑class engineering cultures—and who are ready to apply that craft to one of the most data‑rich problem spaces in the world.
• Unmatched data. Access to proprietary financial services datasets from the world’s largest banks—the kind of signal that powers transformative AI in fintech.
• Real autonomy. You own AI product and delivery for the commercial org. Define the architecture, set the technical direction, ship solutions that move revenue.
• High‑performing, senior‑sponsored team. You’ll partner directly with the Head of AI Strategy to translate vision into production systems. This team has executive air cover and a mandate to move fast.
• Flexibility by design. 1–2 days in office to build team cohesion; remote the rest. We optimize for output, not attendance.
• Compelling compensation. We know how much value your team will bring to FIS and are prepared to make a similar investment in you.

What Sets You Apart

• Production AI at scale. 8+ years in AI/ML engineering, applied machine learning, or advanced analytics—track record of taking models from prototype to production in large, complex environments.
• Technical depth across modern AI. Deep expertise in ML algorithms, neural networks, large‑scale architectures, and modern frameworks. Hands‑on experience with Generative AI, Agentic AI, LLMs, foundation models, and large‑scale inference.
• Strong engineering fundamentals. Proficiency in Python and SQL. Experience building production‑grade ML systems. Familiarity with Azure or another major cloud platform and MLOps pipelines.
• Cross‑functional influence without positional authority. Demonstrated ability to lead through influence across engineering, product, data platform, and business stakeholders—not just within your own team.
• Product‑minded delivery. You think in terms of user outcomes and business impact, not just model accuracy. You naturally ask “what problem are we solving?” before “what algorithm should we use?”
• Bias toward shipping in ambiguity. Comfort operating without a perfect spec. You run fast discovery cycles, ship MVPs, learn, and iterate—especially in organizations where AI maturity is still evolving.
• Executive communication. Ability to simplify complex technical concepts for business audiences and present confidently to senior leadership.
• Bachelor’s degree in Computer Science, Engineering, AI, Machine Learning, or related field (required).
• Master’s or PhD in AI/ML, Computer Science, or related discipline (preferred).

What We Offer You

• A rare opportunity to shape enterprise AI at one of the world’s most influential fintech companies.
• Direct access to massive, proprietary financial services datasets.
• Hybrid flexibility with a high‑trust, output‑driven culture.
• Competitive total compensation package.
• Inclusive, diverse team environment with professional and personal development support.