Thomson Reuters
Risk and Compliance
RiskSolutionsEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“Risk Solutions Engineer at Thomson Reuters. Skills: AI-Powered Solutions, Risk Intelligence Platforms, Automated Controls, Data-Driven Decisioning. Design, develop, and deploy intelligent workflows. automation solutions”
What You'll Achieve.
transform how risk is identified, monitored, and managed across the enterprise; operationalize a proactive, forward-looking risk capability; embedding core operational risk management principles; enable near real-time risk monitoring and insight generation; support enterprise-wide risk visibility; strengthen risk mitigation effectiveness; ensure alignment with established operational risk methodologies; identify emerging risks, anomalies, trends; support ongoing monitoring of key risk indicators (KRIs), control effectiveness, and risk appetite thresholds; enabling leadership forums to focus on critical risk signals and deviations; ensure all solutions adhere to Responsible AI principles; Integrate outputs into Enterprise Risk Management (ERM) processes; ensuring traceability of risk decisions and alignment with audit and assurance expectations; drive adoption of technology-enabled risk management practices; supporting the embedding of a consistent risk-aware culture
Industry & Context.
Ability to break down complex, ambiguous problems into clear, structured technical and analytical solutions; quantitative and analytical mindset; experience deriving actionable insights from data
What They're Looking For.
Must Have
hands-on experience in programming (e. g. , Python, Java), proven track record of building and deploying scalable applications, automation solutions, or data pipelines, Experience in designing data architectures, integrating multiple data sources, ensuring data quality and reliability, Demonstrable experience or working knowledge of AI/ML techniques, NLP, LLMs, anomaly detection, Experience applying AI to real-world problems, unstructured data analysis, predictive modelling, intelligent automation, understanding of enterprise risk management concepts, risk identification, assessment, controls, KRIs, issue lifecycle management, Ability to translate risk frameworks and control logic into data models, automated monitoring solutions, and system-driven controls, Experience or working knowledge of operational risk management practices, risk assessments, control testing, issue management, KRIs, demonstrated ability to rapidly upskill in these areas, Ability to break down complex, ambiguous problems into clear, structured technical and analytical solutions, quantitative and analytical mindset, experience deriving actionable insights from data, link analytical outputs to risk scenarios, control effectiveness, and operational risk outcomes, Excellent verbal and written communication skills, ability to explain complex technical concepts to non-technical audiences, data storytelling capability, influence senior stakeholders, support decision-making, Demonstrated ability to take ownership and drive initiatives end-to-end, concept and design through to implementation and continuous improvement, Experience working cross-functionally, operating effectively in a fast-paced, evolving environment, Curious, forward-thinking, comfortable experimenting with emerging technologies and new approaches, High degree of adaptability, ability to pivot based on evolving business priorities and technological advancements, Demonstrated ability and willingness to build expertise in operational risk frameworks, risk taxonomy, and enterprise risk management processes
Nice to Have
Senior title preferred
What You'll Do.
and deploy intelligent workflows
Build and maintain data pipelines
modular components and platforms
Convert risk taxonomy
and issue management frameworks into machine-readable rules
monitoring mechanisms
Design and embed preventive and detective controls within systems
Develop predictive analytics and modelling capabilities
Deliver decision-ready insights through BI dashboards
Ensure all solutions adhere to Responsible AI principles
Integrate outputs into Enterprise Risk Management (ERM) processes
How You'll Work.
Team & Collaboration
Partnering closely with Risk, Technology, and Data teams; Serve as a technical liaison between Risk, Compliance, Technology, and Data teams; translating complex analytical outputs into actionable business insights; Use data storytelling to influence decision-making; drive adoption of technology-enabled risk management practices; supporting the embedding of a consistent risk-aware culture across business and technology teams; Experience working cross-functionally
Communication Scope
Excellent verbal and written communication skills; ability to explain complex technical concepts to non-technical audiences; data storytelling capability
Process & Methodology
take ownership and drive initiatives end-to-end
Full Job Description
As a content-driven technology company, Thomson Reuters operates in a uniquely complex and regulated environment and is evolving toward a real-time, data-driven risk and compliance model, moving beyond periodic, retrospective processes toward intelligent, automated systems. This role is a foundational capability builder within the Risk & Compliance function, responsible for architecting and delivering AI-powered, scalable solutions that transform how risk is identified, monitored, and managed across the enterprise. You will operate at the intersection of technology, data, and risk management, partnering closely with Risk, Technology, and Data teams to operationalize a proactive, forward-looking risk capability while embedding core operational risk management principles, including risk identification, assessment, control design, and issue lifecycle management within technology-driven solutions. **About the Role:** **Key Responsibilities:** **Build AI-Powered Risk Solutions** * Design, develop, and deploy intelligent workflows, automation solutions, and AI-driven agents to detect, analyse, and monitor risks across structured and unstructured data. * Apply techniques such as Natural Language Processing (NLP), machine learning, and LLMs to translate regulatory content, operational data, and external signals into actionable risk insights with a focus on identifying operational risk exposures, control gaps, and early warning indicators aligned to enterprise risk taxonomy. **Engineer Scalable Risk Intelligence Platforms** * Build and maintain data pipelines, models, and architectures that enable near real-time risk monitoring and insight generation aligned to enterprise risk needs. * Develop reusable, modular components and platforms that scale across business units and support enterprise-wide risk visibility. **Translate Risk Frameworks into Automated Controls** * Convert risk taxonomy, control requirements, and issue management frameworks into machine-readable rules, aut
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