Jobs at Thomson Reuters

Lead design, implementation, administration, and hardening of enterprise Active Directory and hybrid identity (Entra ID) environments. Own federation, Entra ID Connect, MFA/Conditional Access, AD replication/authentication troubleshooting, automation with PowerShell, DR/HA readiness, and identity modernization. Provide senior escalation, mentor junior engineers, support M&A identity integrations, and drive compliance, security, and operational improvements.

Lead complex customer engagements from discovery through production delivery by architecting, building, and deploying AI solutions. Write and review production code, guide senior engineers, make architecture and deployment decisions, and translate customer-specific learnings into scalable CoCounsel product capabilities. The role requires hands-on expertise in generative AI, LLM systems, enterprise integrations, distributed systems, cloud architecture, security, reliability, and production operations, along with strong technical leadership and customer communication.

Designs, builds, and deploys production-grade AI applications and services for enterprise customers. Responsibilities include customer discovery, AI architecture, software development, APIs, integrations, deployment, observability, evaluation, MLOps/LLMOps, security, governance, and production support. The role also develops reusable frameworks, participates in design reviews, mentors engineers, and leads solutions across the full lifecycle from problem discovery through deployment.

Leads the design and development of cloud-native platforms supporting generative AI agents. Responsibilities include building backend services, developer enablement tools, CI/CD pipelines, Kubernetes and multi-cloud infrastructure, platform security, observability, DORA metrics, and production engineering practices. The role requires mentoring, architectural leadership, cross-functional collaboration, and expertise in cloud-native systems, networking, infrastructure as code, and systems programming.

Own the roadmap and customer discovery for CoCounsel’s expansion into in-house legal departments. Lead a team of product managers, translate legal customer needs into prioritized use cases, and partner with Engineering, Design, Marketing, and go-to-market teams to deliver products. The role requires product management or in-house legal operations experience, generative AI familiarity, customer empathy, and the ability to assess technical feasibility.

Own the transactional use-case roadmap for CoCounsel, translating deal-lawyer needs into prioritized product plans. Lead two to three product managers, guide discovery and prioritization, and partner with Engineering, Design, Marketing, and go-to-market teams to launch solutions for M&A, financing, real estate, capital markets, diligence, drafting, and negotiation workflows.

As a Lead Applied Scientist, you will define research strategy, mentor teams, and innovate AI/ML solutions for legal and other professional sectors.

Designs, develops, tests, deploys, and supports enterprise integrations using Boomi across SaaS, AWS, and on-premises systems. Responsibilities include API development, connector and process troubleshooting, data mapping, performance monitoring, incident resolution, documentation, stakeholder collaboration, and mentoring junior engineers. The role requires expertise in REST, SOAP, JSON, XML, integration patterns, message queuing, and high-volume enterprise integrations.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Design, develop, deploy, and support scalable cloud-native backend services, REST APIs, microservices, and distributed applications. Own solutions across the full software development lifecycle, including database optimization, automated testing, observability, troubleshooting, and production support. Collaborate with cross-functional teams on architecture and technical decisions, improve platform reliability and performance, and mentor engineers through code reviews, guidance, and knowledge sharing.

Build and maintain predictive models, including propensity-to-upgrade and engagement scoring, to drive AI product adoption and customer expansion. Develop features from product, behavioral, campaign, learning, and firmographic data. Partner with Marketing, Customer Success, Data Engineering, Product, and Commercial teams to operationalize models in Treasure Data and activation workflows. Monitor model performance, support experimentation, measure lift, document methodologies, and communicate insights to technical and nontechnical stakeholders.

Leads an AI-first product operations office across Thomson Reuters’ TAAP portfolio. The role automates coordination, dependency tracking, reporting, and communications; advances AI maturity through shared infrastructure, agentic workflows, playbooks, and modern product development practices; and drives organization-wide change. Responsibilities include managing a senior product operations team, enabling product managers, coordinating cross-functional commitments, supporting customer migrations, establishing business metrics, and leading communications and cultural transformation across product, engineering, design, and customer success.

Lead the engineering team for a search platform at Thomson Reuters, focusing on building, operating, and evolving the infrastructure while managing a team of software engineers and aligning efforts with business priorities.

Lead product strategy and roadmap to enter Financial Services for Noetica. Define customer requirements, design data-intensive features, partner with engineering, GTM and sales, and drive commercial growth and integrations to scale the product for fund managers, credit managers, and treasuries.

Lead architecture and implementation of AI-first backend and orchestration systems for Audit Suite. Drive scalable, reliable AI workflows (LLM integration, retrieval, vector stores), mentor engineers, set technical direction, and collaborate across product, design, and ML to deliver auditable, high-throughput document-centric solutions.

Lead the Customer Files Orchestration engineering team and own its distributed service end to end, including file upload, storage, extraction, embedding, indexing, APIs, queuing, reliability, and operations. Hire, coach, and develop engineers; establish team processes, on-call, SLOs, and incident practices; set technical direction and roadmap; and partner with product, platform, storage, document understanding, and indexing teams to scale a reliable, API-first service.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

As a Senior Software Engineer, Full Stack, you will build backend services and APIs for a document analysis platform, focusing on server-side architecture and data processing, while also contributing to frontend features as needed.

Lead the development of AI-powered solutions, drive technical strategy and innovation, mentor engineers, and ensure quality and operational excellence.

Lead strategy, architecture, development, integration, and full lifecycle implementation of Conga CPQ, Turbo Price, Digital Commerce, and PROS Pricing solutions on Salesforce. Establish engineering standards, conduct code reviews, mentor developers, evaluate technologies, resolve complex issues, and ensure scalable, stable systems. Collaborate with architects, technical leads, cross-functional teams, and third parties while managing estimates, dependencies, risks, Agile delivery, and AI-enabled Agentforce capabilities.