Job Description

Are you passionate about transforming the future of legal research with AI? Join our Global Westlaw Engineering organization and help shape the next generation of intelligent legal research solutions.

The Global Westlaw Engineering organization builds and operates the technology that powers Westlaw, the world’s leading legal research platform. Our teams develop innovative products and AI-driven solutions that help legal professionals find trusted answers, uncover insights, and make confident decisions faster. Working across engineering, AI, data, platform, and product disciplines, we deliver secure, scalable, and intelligent experiences for customers around the globe.

As an AI Staff Engineer, you will help define and build the AI foundation that powers the next generation of Westlaw experiences. You will work on cutting-edge technologies including agentic systems, retrieval-augmented generation (RAG), AI platforms, and large-scale knowledge services, enabling teams across Westlaw to deliver intelligent, trustworthy, and high-performing solutions for legal professionals worldwide.

Key Responsibilities

- Build and architect AI-driven systems – Design and lead the implementation of enterprise-scale AI systems, including multi-component pipelines, retrieval-augmented generation (RAG) and knowledge graph-based architectures, and autonomous AI agents with multi-step reasoning; stay hands-on across the stack, from AI orchestration and RAG through API gateways, microservices, and modern web UIs.




- Drive innovation and technical strategy – Evaluate and drive adoption of emerging AI techniques; run proof-of-concept work and assess technical feasibility for new AI-driven features; stay current with AI research and translate insights into technical roadmaps; represent the organization at industry conferences and events.
- Provide technical leadership – Help make design decisions and translate business requirements into scalable technical specifications; mentor senior and junior software engineers; champion MLOps and LLMOps practices and governance for the AI model lifecycle.
- Ensure quality, security, and operational excellence – Design and implement testing, monitoring, and observability for AI systems at scale; ensure compliance with ethical AI principles, security standards, and regulatory requirements.
- Lead cross-functional collaboration and drive business value delivery – Partner with AI researchers, engineering leadership, design, and product to turn AI capabilities into customer-facing applications; set technical priorities and stay engaged through delivery so AI investments produce measurable business value; optimize performance for latency, cost, and user experience; influence product strategy through technical depth.

Required Qualifications

- Bachelor’s degree in Computer Science, Engineering, or equivalent experience (Master’s preferred).
- 5+ years of software engineering experience, including 3 years in senior or lead roles on AI/ML systems.
- A track record as a software engineer with AI expertise (not primarily a data scientist or researcher),



with hands-on experience in generative AI, RAG, or LLM-based systems, covering discovery, architecture, agentic tools, evaluation, deployment, and metrics.
- Expert-level proficiency in Python or another object-oriented language, with robust backend service and API design skills.
- Solid understanding of ML principles, evaluation methodologies, and distributed systems, plus working experience with AI/ML frameworks (e.g., PyTorch, TensorFlow).
- Advanced experience with AWS and with Docker, Kubernetes, and Terraform, and a record of integrating AI models into large-scale production systems through APIs, data pipelines, and cloud-native architectures.
- Strong technical leadership and mentoring experience as an individual contributor, with the communication skills to influence senior stakeholders.

Preferred Qualifications

- Experience leading technical direction for teams building agent-based systems or enterprise integrations with AI APIs (e.g., OpenAI, Anthropic).
- Advanced knowledge of vector databases, embeddings, semantic search, and information retrieval.
- Hands-on experience with knowledge graphs, including graph data modeling, ontologies and taxonomies, graph databases (e.g., Neo4j, Amazon Neptune), and combining graphs with LLMs through approaches such as GraphRAG and entity extraction.
- Domain expertise in legal, tax, accounting, or other regulated industries, or in large-scale search platforms.
- Successful AI product launches and experience scaling AI systems to enterprise customers.
- Experience with AI governance, model risk management, and regulatory compliance.
- Publications, patents, or speaking experience in AI/ML.Jon<

📌 Staff Software Engineer (Toronto)
🏢 Thomson Reuters
📍 Toronto