Retrieval is the ceiling on everything above it. An agent working a legal, tax, or regulatory question is only as good as the evidence handed to it, whether it can find the controlling authority in a corpus of millions of documents, weigh sources that conflict, and be honest about what it doesn't have. Every higher-order capability we ship depends on retrieval being trustworthy first.

This role, in TR Labs, owns the engineering behind that layer: next-generation search and retrieval serving both traditional search experiences and agentic AI workflows over large collections of legal, tax, and regulatory content. What makes this research engineering rather than software engineering is that the answer isn't known when you start. You form the hypothesis, isolate the variable, read the numbers honestly, and kill the idea when the data says to.

Then you do the part many researchers don't: make the winning version production-grade, ship it, and keep it healthy. You will work shoulder-to-shoulder with applied scientists, building on their models and research directions and feeding production evidence back into the science. You reach for a baseline, an ablation, and a control before you trust a result, and you have the taste to know which experiments are worth running and which are not.

You build with AI tooling rather than around it, and you bring the same skepticism to what a coding agent hands you as to what an experiment tells you. Given a messy project, you can work out what the most impactful next thing to do is and go do it. You can explain your work to engineers, scientists, and product stakeholders alike: defend a design choice, and update on evidence when someone shows you a better one.

Own end-to-end delivery of significant search and retrieval projects, accountable for the outcome, the quality and timeline, and the system once it is live Act as technical lead for a squad of 3–5 engineers: set direction, break down the work, review designs and code, and unblock the team Partner closely with applied scientists, build on their models, ranking approaches, and research directions, and feed production evidence back into the science Design and build retrieval architectures, ingestion and indexing pipelines, and ranking and re-ranking systems on OpenSearch and Vespa Build the retrieval infrastructure that agentic AI workflows depend on, and the search agents themselves: tool-facing retrieval APIs, agentic query planning and multi-step retrieval, RAG pipelines, hybrid and semantic retrieval, and query understanding Build evaluation that actually discriminates — offline relevance harnesses, golden and labeled sets, online A/B tests, and end-to-end agent quality measurement designed to separate real improvement from a number that happened to move, and to keep discriminating as the models get stronger Diagnose retrieval and agent quality failures: why is this result wrong, which stage of the pipeline caused it,



and what does that imply about the design Build and operate production APIs and backend services on AWS, with the performance, reliability, and cost characteristics that mission-critical systems require Identify and communicate risk to timelines and architecture early and clearly, to peers and to senior stakeholders Bachelor's or Master's in Computer Science, Engineering, or a related field ~~7+ years building production software, including search, retrieval, or ranking systems you shipped and then owned — launched, scaled, and maintained, not just prototyped ~ Proven track record leading technical projects and delivering through other engineers, and influencing architecture decisions across teams ~ Deep hands-on production expertise in OpenSearch or Vespa (or comparable depth in Elasticsearch, Solr, or Lucene, with the ability to ramp on ours) rather than only consuming a vector database or a retrieval API ~ Rigor with evidence: designing search experiments, relevance and ranking metrics, offline evaluation harnesses, online A/B measurement — and the discipline to know when a result is real ~ Outstanding software engineering in Python, across the stack from ingestion pipelines to retrieval services to evaluation infrastructure ~ AI-native development: agentic coding tools are a routine part of how you build, and you have judgment about where they make you faster and where their output needs checking before it ships ~ Designing, operating, and scaling production APIs and large-scale distributed systems on AWS, including performance optimization at scale ~ Track record of collaborating with applied scientists or ML practitioners and productionizing their models and approaches Retrieval systems and search agents purpose-built for agentic AI workflows Kafka, event-driven architectures, and large-scale data pipelines ML infrastructure, embedding pipelines, and vector databases Experience with legal, regulatory, tax, scientific, or other text-heavy domains Our use of AI within the recruitment process Thomson Reuters utilizes Artificial Intelligence (AI) to support parts of our global recruitment process. Unless you opt-out, our AI system will assess the information provided by you and compare it to the requirements listed for the role, and present the result to our recruitment personnel for further review. The AI system acts as a supporting tool, but there is always a human making the decision if you will be considered for the role.

Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition,



Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws.

Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&D; insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. Eligible office location(s) for this role include one or more of the following: Base pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.

Thomson

Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency.

Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in versatile work environments. Join us and help shape the industries that move society forward.

To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law.

Thomson

Reuters makes reasonable accommodations for applicants with disabilities, including veterans with disabilities, and for sincerely held religious beliefs in accordance with applicable law. Disability accommodations in the recruiting process may include things like a sign language interpreter, making interview rooms accessible, providing assistive technology, or other relevant accommodations.

📌 Lead Research Engineer, Search & Retrieval (Toronto)
🏢 PowerToFly
📍 Toronto