Director, Risk & Compliance Engineering & Assurance

As a content-driven technology company, Thomson Reuters operates in a uniquely complex and regulated environment and is maturing risk and compliance management towards intelligent, automated, and agentic systems underpinned by data to drive accountability and speed in decision making. The Director, Risk Engineering & Assurance is a pivotal leadership role in this journey.

• About the Role
• As Director, Risk and Compliance Engineering & Assurance, you will:
• •Set the technical strategy . Own the AI strategy, foundations, and engineering roadmap for Risk & Compliance, setting the technical direction for how the function adopts and scales AI, automation, and agentic workflows to enable our by-design and assurance ambitions.
• •Deliver the data products . Build, publish, and continuously improve governed risk, compliance, privacy and resilience data products, curated collections of signals from across key areas within Thomson Reuters.
• •Modernise TPRM and partnerships . Mature the automation and agentic-AI capabilities for third-party due diligence (supplier and customer), partnerships due diligence, compressing cycle times while strengthening, not weakening, the quality of assessment and enhancing continuous monitoring.
• •Automate assurance . Lead the use of technology and AI to further mature automated Assurance work, in particular controls testing, moving from sample-based, manual testing toward continuous, evidence-led assurance.
• •Build a world-class team . Build and develop the existing team into a world-class forward-engineering function, defining the people, processes, and technology capabilities, the skills, competencies, ways of working, and tooling, needed to deliver at pace.
• •Engineer for trust . Ensure every solution is enterprise-grade and aligned with Responsible AI, data governance, access control, and the firm's fiduciary-grade standards, so stakeholders trust the outputs enough to act on them.

About You

You’re a fit for the role of Director, Risk & Compliance Engineering & Assurance, if you have the following required qualifications:

You are an engineering and AI leader who builds teams and ships at scale. You have led technical teams that deliver production-grade software, data, and AI, and you can set direction in ambiguity and translate complex business problems into scalable, well-governed solutions. You are as comfortable making architecture and build-versus-buy decisions as you are coaching your team, shaping a roadmap with senior stakeholders, and holding delivery accountable.

You do not need to be a career risk professional. Deep risk, compliance, or audit domain knowledge can be developed over time, and the team includes that expertise. What is essential is proven engineering leadership, strong AI and data foundations, and the judgement to embed sound risk and control principles into what you build. You lead with a bias to enable: you find the safe, fast path to yes and treat the function as a catalyst for accountable growth, not a brake.

• What We Are Looking For
• Engineering & Technical Leadership
• •Substantial experience leading software engineering, data, or AI/ML teams, typically 12+ years of relevant experience with several in a leadership capacity, delivering production-grade solutions at enterprise scale.
• •Strong hands-on foundations in modern data and AI engineering (for example Python, SQL, cloud-native platforms, data pipelines), enough to set technical direction credibly and make sound architecture decisions.
• •Demonstrated experience with AI/ML technologies, including LLMs, Retrieval Augmented Generation (RAG), agentic workflows, Natural Language Processing (NLP), and predictive analytics, and the discipline to run them reliably in production.
• •Track record of building on shared enterprise data platforms (for example Snowflake) and delivering through modern interfaces such as MCP, rather than building parallel infrastructure.
• Team Building & People Leadership
• •Proven ability to build, grow, and retain a high-performing teams, defining roles, skills, and competencies, and developing existing talent into a world-class capability.
• •Experience designing the operating model of a technical team, its ways of working, delivery cadence, quality standards, and tooling, in a product operating model context.
• •A coaching leadership style that raises the technical bar while creating an environment where the team do their best work.

• Risk, Assurance & Automation Domain
• •Experience automating risk, compliance, or assurance processes with technology and AI, third-party or customer due diligence, monitoring, or controls and controls testing e.g. enterprise control testing is a strong advantage.
• •Understanding of how to embed risk identification, control design, and issue lifecycle management into technology solutions, so automation strengthens the control environment.

• Responsible AI & Governance
• •Understanding of Responsible AI practices, model governance, data access control, and privacy-by-design, with the ability to hold solutions to TR`s standards.
• •Ability to determine and implement how AI subscribes to sensitive signals and to assure the reliability of AI-generated insight, including monitoring, drift detection, and graceful handling of failed data feeds.

• Business Partnering & Influence
• •Strong communication skills and the ability to explain technical and AI concepts to non-technical senior audiences.
• •Experience partnering with senior business and technology stakeholders to translate needs into products, and influencing decisions through data, insight, and clear storytelling.
• •Commercial judgement and a bias to enable: framing risk so leaders can act, holding owners accountable across functions the team does not control, and finding the safe path to yes.

• Key Leadership Responsibilities
• •Strategy & roadmap . Set and own the Risk & Compliance AI and data-product strategy and roadmap, aligned to Risk and Compliance vision and mission.
• •Team & capability . Lead the forward-engineering central team and its hiring, and capability development.
• •Platform partnership . Establish the rent-not-build partnership with the Data & Analytics organisation and the shared-service model that serves Risk and Compliance.
• •Delivery . Deliver priority data products and automation.
• •Operating disciplines . Own the data-product operating disciplines, product management, semantic and taxonomy ownership, and AI access and insight assurance.
• •Outcomes . Measure and report success by decision-influence and accountability outcomes, not build volume.

• Key Relationships
• •Within Risk : VP Risk (line manager) and the Risk partnering directors across Enterprise Risk & Policy Governance, GTM, Operations, Technology & Data, TPRM, and Assurance & M&A.
• •Across Risk & Compliance : Compliance, Privacy, and Resilience as co-consumers of the shared data-product estate.
• •Across TR : Legal, Data & Analytics, CTO, Product, CIO and wider CDO organisations, and Internal Audit.

• Technologies You'll Work With
• •LLMs and agentic frameworks
• •RAG architectures
• •AI agents and orchestration (e.g. LangChain / LangGraph)
• •Python and modern data engineering
• •Snowflake and governed semantic layers
• •AWS / GCP cloud services
• •Vector databases
• •Data pipelines and MLOps tooling
• •Business intelligence and visualisation tools

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What’s in it For You?

Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.

Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowe