Manager, Software Development Engineering

About the role

The Manager, Software Engineering leads the engineering team responsible for building, operating, and evolving Thomson Reuters’ Content Tools platform. Content Tools are the purpose-built APIs and capabilities that give AI agents precise, reliable access to TR’s most valuable legal content.

Responsibilities

• Own the end-to-end engineering roadmap for Content Tools — spanning tool design and implementation, CLI and SDK exposure, CI/CD pipelines, evaluation infrastructure, and cloud operations — balancing new capability delivery with rigorous quality and reliability standards
• Drive an API-first, contract-driven approach to tool development: every tool ships with a versioned CLI contract, schema, and clear ownership metadata that makes it discoverable and usable by consuming teams without direct engineering involvement
• Establish and enforce the patterns, templates, and contribution standards that allow distributed teams to build and contribute tools consistently — including review workflows, quality gates, namespace governance, and guidance on when to create new tools versus extend existing ones
• Lead the build-out of the information retrieval (IR) evaluation framework, ensuring every tool is validated against representative datasets before release and that performance regressions are caught automatically in CI/CD
• Champion full-stack operational ownership: the team defines, builds, tests, deploys, and operates what it ships — including on-call rotations, SLO definitions, incident response, and health monitoring for production tool services
• Partner closely with TR Labs and CoCounsel Engineering teams to ensure content tools meet the interface requirements of agentic workflows — covering tool invocation patterns, result provenance
• Build and lead a team of approximately 10 software engineers (including Senior and Staff levels), managing hiring, onboarding, performance, and professional development with a focus on deep technical ownership
• Translate complex content technology concepts for non-technical stakeholders — making the value and trade-offs of Content Tools investments legible to product managers, business leaders, and partner teams
• Model and reinforce AI-assisted development as a team norm: more than 50% of code written with AI assistance is the target, not a stretch goal
• Define and maintain engineering processes for a team that both builds shared tool infrastructure and delivers production content capabilities — ensuring rigorous testing, code review, and continuous evaluation of tool quality through offline IR grading pipelines and online signals
• Evaluate and integrate emerging tool protocols (including MCP support) and retrieval patterns, with a clear-eyed view of production-readiness and operational implications
• Cultivate strong working relationships with Labs, Product, and CoCounsel Engineering — engaging early in agentic workflow design to ensure content tools are shaped to the access patterns agents actually need
• Collaborate across the organization to align the Content Tools roadmap with business priorities in CoCounsel Legal

Requirements

Required Experience: - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field - 6+ years of software engineering experience, with at least 2 years in a technical leadership or engineering management role - Demonstrated experience designing and operating API-first systems consumed by multiple teams, with a product mindset toward developer experience and internal customer satisfaction - Proficiency in Python and strong software engineering fundamentals, API design, testing strategy (unit, integration, and IR/evaluation), and CI/CD practices - Experience building and governing shared platform infrastructure in a distributed development model — including contribution standards, versioning policies, and cross-team coordination - Familiarity with information retrieval concepts — including precision/recall trade-offs, hybrid search, citation networks, and document retrieval patterns — sufficient to make sound architectural decisions and partner effectively with scientists - Proven ability to lead teams that own their production systems end-to-end, including on-call responsibilities, SLO management, and incident response - Strong leadership skills: experience in agile methodologies, excellent communication, and the ability to build alignment across engineering, product, and science teams - Awareness of AI ethics, content licensing considerations, and responsible deployment of retrieval systems Preferred Experience: - Experience building tools or APIs for agentic AI systems, including familiarity with tool protocols such as MCP (Model Context Protocol) or similar - Background in legal technology, knowledge management, or other high-stakes information retrieval domains where provenance, accuracy, and entitlement enforcement are critical - Hands-on experience with search and retrieval infrastructure (e.g., Elasticsearch, Vespa, OpenSearch) and the trade-offs between semantic and structured search - Experience with evaluation frameworks for retrieval systems, including dataset design, IR metrics (Precision, Recall, NDCG, etc.), and CI/CD integration of quality gates - Familiarity with content access control, policy-based entitlements, and licensing enforcement in multi-tenant environments - Experience operationalizing tooling for LLM-powered workflows, including prompt engineering, tool description design, and agent invocation patterns