Director of Platform, AI & Data

Reporting to the CTO with a dotted line into the CPCO, this role owns the strategy and execution across Product and Engineering for three core domains: Platform, AI, and Data. Accountable for creating, maintaining, and socialising compelling, prioritised roadmaps that align platform and capability supply with product demand, while influencing the product roadmap with clear opportunity, cost, and risk signals. Responsible for adoption and internal sentiment as primary success measures, ensuring we only build capabilities that teams actively use and value. Leads UK and Hyderabad (India) teams and partners, balancing change and run, legacy and modernisation, buy/build/partner choices, and security and compliance requirements.

Key stakeholders

• CTO & Technology SLT
• CPCO, Product Leadership & stream-aligned product engineering teams
• Director of Strategic Insights & Analytics teams
• Senior Engineering ICs - Principal / Staff Engineers, Architects
• Marketing Leadership & teams
• InfoSec, Risk (2LOD), and Compliance
• Finance (budget, FinOps), Procurement, and Vendor partners
• UK&I BUs and global counterparts for reuse and interoperability

Core responsibilities

Product and Portfolio

• Own and socialise a rolling 4-quarter capability roadmap across Platform, AI, and Data; align capacity to product demand and business outcomes.
• Define and track adoption and internal sentiment targets for all capabilities; publish scorecards and retrospectives.
• Operate a transparent intake and prioritisation process balancing regulatory, reliability, and growth opportunities.
• Influence product roadmaps by evidencing platform leverage, reuse, cost-to-serve, and time-to-market impacts.
• Drive clear buy vs. build vs. partner decisions with measurable value and risk trade-offs.

Platform

• Deliver internal platform capabilities that simplify and accelerate product delivery: optimisation, feature toggles, personalisation, alerting, BAU support, and paved-road developer experience.
• Productise platform services and complex subsystems with SLAs/SLOs, APIs, documentation, and clear ownership; reduce cognitive load on product teams.
• Standardise observability, deployment, and release practices; improve lead time, change failure rate, MTTR, and availability.
• Promote reuse across UK&I and global BUs; retire obsolete services and reduce technical complexity.

AI

• Shape the AI domain and establish an AI-forward engineering culture with safe-by-design guardrails, patterns, and SDKs.
• Enable domains to build AI capabilities from within (assistive coding, test generation, summarisation, routing, risk checks) to do more with the same.
• Define model selection, evaluation, and monitoring practices; align with Responsible AI, privacy, and security standards.
• Measure AI adoption and productivity uplift; prioritise use cases with clear ROI and risk controls.
• Build out AI capabilities to power intelligent consumer experiences, including on- and off-property chat integrations to enhance user engagement and service efficiency.

Data

• Execute the data strategy and evolve a best-in-class data ecosystem supporting analytics and ML.
• Embed a data-as-a-product mindset with data contracts, lineage, quality SLAs, and clear ownership in domains.
• Advance data democratisation via self-serve tooling, secure access controls, documentation, and enablement.
• Modernise pipelines and platforms; manage the team through change while maintaining reliability and compliance.
• Ways of working and operations
• Lead geographically distributed teams; grow Hyderabad capability and manage third parties to outcomes.
• Coach Product and Engineering leaders across your domains to drive a high-performance culture and inspire teams.
• Own engineering excellence practices and continuous improvement across SDLC and incident management.
• Partner with Risk, 2LOD, and Security to meet regulatory and audit requirements without slowing delivery.
• Own budget for the three domains and drive FinOps, cost transparency, and unit-economics improvements.
• Occasional travel to Hyderabad and partner locations.

What success looks like

• Adoption: year-on-year increase in active usage of platform capabilities by product teams; deprecation of low-value services.
• Internal sentiment: improved platform NPS/CSAT and developer experience scores across teams.
• Delivery performance: reduced lead time, improved deployment frequency, lower change failure rate, faster MTTR.
• Roadmap health: predictable delivery against quarterly plans with clear replan rationale when needed.
• AI outcomes: measurable productivity uplift and risk-controlled AI usage across domains.
• Data outcomes: higher data product quality, increased consumption, and faster time-to-insight; audited lineage and access controls.
• Complexity and cost: reduced integration complexity, improved reuse, optimised cloud spend and unit economics.

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Who we’re looking for

Skills & competencies

• Proven leadership across Product and Engineering; excellent stakeholder management and communication.
• Portfolio and roadmap management with evidence-based prioritisation.
• Platform product management and developer experience expertise.
• Applied AI engineering and governance literacy.
• Modern data platforms, data-as-product, and data governance practices.
• Financial acumen, vendor management, and partner ecosystems.
• Change leadership in complex, regulated environments.

Experiences

• Senior leadership of multi-domain teams (Platform, AI, Data) in distributed settings.
• Building internal platforms adopted at scale by product teams; setting SLAs/SLOs and measuring sentiment.
• Establishing AI enablement and standards; delivering AI use cases safely.
• Evolving data ecosystems and operating data-as-product; improving data quality and access.
• Balancing buy/build/partner and migrating away from legacy complexity.

Internal Grade: EB6

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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Experian Careers - Creating a better tomorrow together

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Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here