Job description

Job Description Staff Software Engineer — Content Tools Content Tools • CoCounsel Agent Context Overview of the Role The CoCounsel Agent Context team is seeking a Staff Software Engineer to set the technical direction for Content Tools — the purpose-built APIs that give AI agents precise, governed access to Thomson Reuters’ proprietary legal content across various international jurisdictions. Content Tools are the bridge between TR’s authoritative content and the AI products, such as CoCounsel Legal, that depend on them, and they carry high stakes — every result an agent returns must be accurate and grounded in TR’s authoritative content. This Staff Engineer defines how those tools are designed, evaluated, and operated, and sets the patterns that every engineer — on this team and on contributing partner teams — builds against. This is a high-leverage role at the intersection of API design, information retrieval, and agentic systems. Staff Engineers here define what to build and why, not just how: they solve ambiguous problems that span multiple teams and systems, and their work is felt well beyond their own code. The team’s operating principles are non-negotiable. You own your work end-to-end, from the first commit to the production dashboard. You ship to production constantly, and you treat delivery friction as an engineering problem to solve, not a fact of life. You use AI-assisted development as a primary tool, with the majority of code written with AI assistance. And you practice verified spec-driven development: acceptance criteria and an evaluation suite define a tool’s behavior before the implementation exists and gate every change in CI. Because AI writes most of the code, what you truly own is the spec and the eval that verifies it — the eval is the spec, and you are accountable for the outcome, not the lines. The successful candidate brings platform thinking, deep API and evaluation instincts, enterprise-grade security awareness, and a product-minded approach to developer experience — treating each tool’s contract as a product in its own right. Key Responsibilities In this position, you will focus on: Content Tool Architecture & API Ownership Set the technical direction for the Content Tools catalog: define the design patterns, schema templates, and contribution standards every tool is built against, and the guidance on when to create a new tool versus extend an existing one — resolving problems of broad scope with little precedent to guide solutions Drive an API-first, contract-driven approach: every tool ships with a versioned contract, schema, and ownership metadata that makes it discoverable and self-service for consuming teams and agent developers, who should never need to ask you how to use your tool Architect the retrieval and search layer behind the catalog — relevance and ranking quality on the team’s Vespa based search platform, and the trade-offs between structured and semantic retrieval — partnering with TR Labs on the underlying search algorithms Define the agent invocation model for the catalog: clean tool boundaries exposed over MCP (Model Context Protocol), result payloads designed for token economy, and latency budgets that hold across multi-hop retrieval chains, giving agent orchestrators predictable, well-documented interfaces to TR and third-party content Build and own the shared development and testing infrastructure — common libraries, scaffolding generators, mock services, and local environments, built on the team’s Python, FastAPI, and Claude Agent SDK stack — that makes it easy for any team member to build a Content Tool correctly the first time Verified Spec-Driven Development & Evaluation Own verified spec-driven development as a team-wide standard: define how acceptance criteria and evaluation datasets are written before implementation to specify a tool’s behavior, IR metrics (precision, recall, NDCG), and CI gates that verify every change and set the bar every engineer’s eval suite follows Treat evaluation as foundational infrastructure the team is still maturing: assess current coverage across tool families, close the highest-risk gaps first, and prevent teams from redundantly reinventing evaluation capability Define how offline grading pipelines and online signals combine into a continuous, trustworthy quality picture for every tool in production Reliability & Operations Take full operational responsibility for what you and your area own — you built it, you own it, you run it: own the on-call model and SLO targets for your services, and build the automation that reduces operational toil for the whole team Lead incident response for high-severity issues, write thorough post-mortems, and drive systematic fixes that prevent recurrence Build the observability that makes reliability visible — including trace-level instrumentation for agentic retrieval paths, where standard request/response logging cannot explain a non-deterministic failure Own performance and cost strategy for the tool layer: capacity planning, caching, and rate limiting that keep the platform reliable and economical as tenants, content volumes, and query traffic grow, with fast, safe delivery treated as a first-class engineering goal rather than a trade-off against reliability Technical Leadership & Governance Function as the technical authority other engineers and partner teams turn to for Content Tools API, evaluation, and architecture decisions; author cross-team Architecture Decision Records for cross-cutting choices and contribute to the code- and design-review policy the team follows Multiply the team: develop Senior engineers through architecture guidance, design pairing, and constructive review, with measurable growth in the people you mentor — your impact is the patterns you set and the engineers you grow Build durable relationships with the teams that depend on you — CoCounsel Engineering, TR Labs, and product owners — , feeding structured requirements back into the roadmap, and reducing time-to-value for new adopters Establish team-wide AI-assisted development patterns and model them visibly; capture decisions in writing where the team can find them, so work is legible to async readers Make the hard calls: say no to unnecessary complexity, advise senior leadership on complex , and champion ethical AI and responsible, secure deployment across the team’s work You’re an ideal fit if you have: Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field 8 years of software engineering experience with demonstrated progression to staff-level or equivalent technical leadership — including ownership of a functional area and leadership of significant cross-team initiatives Mastery of Python and strong fundamentals across API design, testing strategy (unit, integration, load and evaluation), system design, and security architecture Track record of designing and operating API-first systems consumed by multiple teams, with a product mindset toward developer experience — including versioning, backward compatibility, and clear contracts Working fluency with information-retrieval concepts (precision/recall trade-offs, hybrid search, ranking, citation networks) sufficient to make sound architectural decisions and partner credibly with research scientists Demonstrated experience designing or owning evaluation frameworks for retrieval or LLM systems: dataset design, IR metrics, CI-gated eval suites, and tracing and observability for non-deterministic workflows Proven reliability ownership at the system level: designing on-call models, setting SLOs, leading incident response, and a clear philosophy that shipping frequently and operating reliably are complementary, not in tension Demonstrated security and access-control practice: Fluency with AI-assisted development tools; you write the majority of your code with AI assistance, produce higher-quality work because of it, and establish the patterns that help the team do the same Strong communication: you explain complex retrieval and architecture concepts to technical and non-technical audiences and build alignment across engineering, product, and science Preferred Qualifications Experience building tools or APIs for agentic AI systems, including tool protocols such as MCP (Model Context Protocol) or similar Background in legal technology, knowledge management, or other high-stakes information domains where source attribution, accuracy, and entitlement enforcement are critical Hands-on experience operating search and retrieval engines (OpenSearch, Vespa, Elasticsearch) — cluster sizing, index lifecycle, and the trade-offs between semantic and structured search Experience operationalizing tooling for LLM-powered workflows: tool-description design, prompt engineering, and agent invocation patterns Experience establishing contribution governance for a platform built on by multiple teams — review workflows, registry/namespace management, and deprecation and migration policies Familiarity with content licensing and policy-based entitlements in multi-tenant environments Working understanding of infrastructure-as-code (Terraform) and API gateways (such as Apigee) — enough to operate, secure, and reason about the services you own What Success Looks Like In the first 90 days: Develop a comprehensive mental model of the Content Tools architecture — tool inventory, CI/CD pipelines, evaluation infrastructure, and the legacy dependencies and migration paths in flight — and identify the top architectural risks and debt items across the team’s systems by shipping multiple tools Establish working relationships with CoCounsel Engineering, Product, and TR Labs, understanding each stakeholder’s priorities and integration pain points firsthand Establish your AI-assisted development workflow and model it visibly for the team; take on-call ownership for your functional area Ship at least one high-impact improvement that demonstrates judgement and taste, not just velocity, and assess eval coverage across tool families to pinpoint the most urgent gaps In the first year: Drive the architecture for a major Content Tools initiative — a significant catalog expansion, the evaluation framework, or a comparable platform milestone — from design through production, establishing the patterns and templates other engineers build against Establish Content Tools as a well-documented, measurably reliable internal platform: verified spec-driven development as the default, SLO coverage across core services, automated eval gates in CI, on-call runbooks, and a track record of fast, high-quality incident resolution Multiply the team: at least two Senior engineers have grown measurably through your architecture guidance, design pairing, and mentorship Be recognized across the organization as the Content Tools architecture authority — shaping team standards, influencing cross-team architecture, and advising leadership on complex #LI-SM2 This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization. What’s in it For You? Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact:  We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. 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. In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. 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; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption & Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan. Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations. For any eligible US locations, unless otherwise noted, the base compensation range for this role is $118,400 USD - $219,800 USD. For Ontario, Canada, the base compensation range for this role is $140,600 CAD - $190,600 CAD. 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. About Us 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 flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. 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 is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. Thomson Reuters makes reasonable accommodations for applicants with disabilities, including veterans with disabilities, and for sincerely held religious beliefs in accordance with applicable law. If you reside in the United States and require an accommodation in the recruiting process, you may contact our Human Resources Department at HR.Leave-Expert thomsonreuters.com . 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. Please note this email is not intended for general recruitment questions and we will promptly respond to inquiries regarding accommodations. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com

Requirements

Must-haves

Staff Software Engineer — Content Tools
Content Tools • CoCounsel Agent Context
Overview of the Role
Content Tool Architecture & API Ownership
Verified Spec-Driven Development & Evaluation
Define how offline grading pipelines and online signals combine into a continuous, trustworthy quality picture for every tool in production
Reliability & Operations
Lead incident response for high-severity issues, write thorough post-mortems, and drive systematic fixes that prevent recurrence
Build the observability that makes reliability visible — including trace-level instrumentation for agentic retrieval paths, where standard request/response logging cannot explain a non-deterministic failure
Technical Leadership & Governance
Build durable relationships with the teams that depend on you — CoCounsel Engineering, TR Labs, and product owners — , feeding structured requirements back into the roadmap, and reducing time-to-value for new adopters
Establish team-wide AI-assisted development patterns and model them visibly; capture decisions in writing where the team can find them, so work is legible to async readers
Make the hard calls: say no to unnecessary complexity, advise senior leadership on complex , and champion ethical AI and responsible, secure deployment across the team’s work
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
8 years of software engineering experience with demonstrated progression to staff-level or equivalent technical leadership — including ownership of a functional area and leadership of significant cross-team initiatives
Mastery of Python and strong fundamentals across API design, testing strategy (unit, integration, load and evaluation), system design, and security architecture

Nice-to-haves

Experience building tools or APIs for agentic AI systems, including tool protocols such as MCP (Model Context Protocol) or similar
Background in legal technology, knowledge management, or other high-stakes information domains where source attribution, accuracy, and entitlement enforcement are critical
Hands-on experience operating search and retrieval engines (OpenSearch, Vespa, Elasticsearch) — cluster sizing, index lifecycle, and the trade-offs between semantic and structured search
Experience operationalizing tooling for LLM-powered workflows: tool-description design, prompt engineering, and agent invocation patterns
Experience establishing contribution governance for a platform built on by multiple teams — review workflows, registry/namespace management, and deprecation and migration policies
Familiarity with content licensing and policy-based entitlements in multi-tenant environments
Working understanding of infrastructure-as-code (Terraform) and API gateways (such as Apigee) — enough to operate, secure, and reason about the services you own
What Success Looks Like

Application prep

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Keywords to mirror

aiapipythonllmci/cd

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off

Parental Leave