Jobs at Thomson Reuters

Design, build, test, and deploy secure cloud-native software and AI solutions for legal workflows. Partner with legal customers to translate needs into scalable products, evaluate LLM outputs, optimize prompts, apply DevOps and infrastructure-as-code practices, manage technical debt, and mentor junior engineers. The role requires strong Python and distributed-systems expertise, legal fluency, client communication, and collaboration across engineering, product, legal, and design teams.

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.

Build and lead a customizable, enterprise-scale search retrieval platform. Responsibilities include designing retrieval APIs and search services, managing ingestion and indexing pipelines, enabling hybrid retrieval and ranking, operationalizing evaluation and observability, enforcing multi-tenant security, owning SLOs and on-call, and partnering with product, research, and applied science teams. The role also sets architectural direction, leads cross-team initiatives, and mentors engineers.

Build and operate Thomson Reuters’ scalable search platform, including document ingestion pipelines, indexing systems, query APIs, cloud infrastructure, and AI-enabled retrieval capabilities. Responsibilities include designing distributed services, migrating from OpenSearch to Vespa, improving observability and reliability, participating in on-call, owning production incidents, mentoring engineers, and collaborating with research scientists and client teams to deliver search and AI features.

Build and deploy production-grade AI solutions for legal workflows, including RAG pipelines, agentic systems, enterprise integrations, evaluation frameworks, and observability. Collaborate with architects, engineers, clients, and legal subject-matter experts to translate legal needs into secure, scalable implementations. Participate in technical discovery, prototyping, demonstrations, prompt engineering, model evaluation, red-teaming, and MLOps/LLMOps lifecycle management.

Design, build, and operate a scalable search control plane managing provisioning, configuration, upgrades, indexing, and retirement across Kubernetes, Kafka, Vespa, and OpenSearch. Own multi-tenant security, observability, SLOs, infrastructure as code, CI/CD, capacity planning, reliability, and incident response. Provide technical leadership, establish architectural standards, lead infrastructure initiatives, partner with client teams, and mentor engineers.

Design, build, and deploy scalable, secure machine learning solutions—with emphasis on recommender systems. Produce design docs and representative models, establish ML best practices and quality control, lead engineering efforts, and collaborate cross-functionally to integrate ML products using cloud, MLOps, and data engineering tools.

Own key areas of the CoCounsel application experience from problem definition through delivery. Shape product strategy and roadmap, improve UX and performance, drive adoption and retention, and lead initiatives such as personalization and collaboration. Partner with product, engineering, customer-facing, legal, IT, security, and operations stakeholders to translate customer needs into experiments, requirements, and measurable outcomes. Develop repeatable UI patterns and documentation while supporting commercial and customer success teams.

Provides technical leadership for generative AI products in Corporate Tax and Trade. Defines software strategies, leads AI-native feature development, integrates LLMs and generative AI, improves Micro Front End scalability and latency, mentors global engineering teams, manages technical risk, and translates business needs into technical solutions. Requires extensive software engineering experience, modern web technologies, cloud platforms, AI/ML integration, enterprise SaaS experience, and advanced education.

Provides technical leadership for generative AI products in Corporate Tax and Trade. Defines software strategies, designs AI-native features, integrates LLMs, optimizes Micro Front Ends, mentors engineering leaders, manages technical risk, and translates business needs into scalable solutions. Requires extensive software engineering experience, modern web and cloud technologies, agentic AI expertise, enterprise SaaS experience, and the ability to lead complex initiatives.

Lead a ~10-engineer team owning the Content Tools platform: design, implement, test, deploy, and operate API-first tooling and governance. Establish contribution standards, CI/CD evaluation pipelines, IR evaluation frameworks, observability, and SLOs. Coordinate cross-team integration with agentic AI workflows and ensure reliability, discoverability, and licensing controls for multi-tenant content access.

Develop and deploy AI-first software applications within an editorial tools team. Translate business requirements into technical designs, build performant and resilient features, integrate APIs, participate in releases, and collaborate with product, QA, operations, and development teams. The role includes testing, debugging, documentation, production support, cloud development, CI/CD, infrastructure-as-code, containerization, and critical validation of AI-generated code.

Leads architecture and delivery of complex, business-critical software systems. Modernizes legacy platforms, designs distributed services, APIs, event-driven architectures, and large-scale data-processing systems, while improving reliability, scalability, security, and observability. Sets technical direction across teams, establishes engineering standards, mentors senior engineers, and partners with product and architecture leadership to connect technical investments to business outcomes.

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.

Leads and develops senior engineering teams delivering production AI solutions for tax, audit, and accounting clients. Owns hiring, staffing, capacity planning, client delivery, technical architecture, AI quality controls, risk mitigation, operating costs, and client outcomes. Oversees LLM applications using RAG, agents, integrations, evaluation frameworks, and observability. Partners with business, product, consulting, and platform leaders to improve engineering effectiveness, manage escalations, and align capacity with demand.

Build and deliver enterprise integrations connecting AI solutions with tax and audit products, ERP systems, document platforms, and data warehouses. Develop document-processing, retrieval, embedding, and vector-search pipelines; enable AI agents through APIs and MCP; and establish data validation and quality controls. Implement secure authentication, testing, monitoring, deployment patterns, and operational runbooks. Partner with clients and cross-functional engineering, platform, consulting, and reliability teams to deliver reusable, production-ready solutions.

Build and deploy secure, production AI applications for tax and audit professionals, including RAG pipelines, custom agents, and agentic workflows. Develop scalable Python backend services, integrate with client and Thomson Reuters systems, and establish evaluation, observability, monitoring, and testing practices. Lead client delivery, translate ambiguous business needs into technical solutions, support deployments and incidents, and collaborate with AI engineers and senior technical leaders across multiple engagements.

Build and deploy reliable AI automations for tax and audit professionals. Responsibilities include understanding client workflows, designing controlled AI solutions, creating prompts and agents, developing prototypes with Python and low-code tools, validating accuracy through expert datasets and test harnesses, demonstrating solutions to clients, and collaborating with domain, editorial, product, and engineering teams. The role requires substantial tax or audit experience, professional judgment, and the ability to translate complex workflows into practical AI applications.

Manages renewals and revenue growth for Canadian small-law clients using Thomson Reuters legal, tax, and AI solutions. Builds long-term client relationships, identifies at-risk accounts, supports renewal and expansion opportunities with Sales Executives, negotiates solutions, educates customers on products and competitors, meets revenue goals, and communicates competitive insights. Requires fluent English and French communication, customer service and sales or account management skills, and proficiency with Microsoft Office.

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.