Senior Manager, Software Engineering -Search Platform

The CoCounsel Legal Integrations team is seeking a Senior Manager, Software Engineering to lead the engineering team responsible for building, operating, and evolving the shared search platform at Thomson Reuters. This platform is the foundation of TR’s search capability — a managed, self-service infrastructure that allows internal client teams to configure, deploy, and iterate on production search systems in days rather than months, accelerating the delivery of high-quality search experiences across TR’s legal, tax, and professional products. The team owns what it builds — defining, building, testing, deploying, scaling, and operating search infrastructure end-to-end. The Senior Manager is responsible for growing this team from its current early stage into a high-performing, product-minded engineering organization that ships to production constantly, treats delivery friction as the first problem worth solving, and holds itself to the same reliability and developer-experience standards as any best-in-class external search platform. The successful candidate brings deep systems and platform thinking, strong people leadership, and the credibility to make hard architectural calls alongside world-class engineers and research scientists. About the Role In this position, you will: Own the end-to-end platform engineering roadmap — spanning document ingestion and processing, search engine management, query APIs, platform control-plane APIs, and the cloud infrastructure that ties them together — balancing new capability delivery with rigorous management of reliability and technical debt Drive API-first, self-service architectural thinking: ensure that every capability the platform delivers is accessible via a clean, versioned, well-documented API, and that internal client teams can configure and operate search systems without direct involvement from the platform team Lead the migration from current search infrastructure to the platform’s strategic search engine, including Vespa adoption, while maintaining zero-downtime operations on existing production systems throughout the transition Champion full-stack operational ownership across the team: the team defines, builds, tests, deploys, scales, and operates what it ships — establishing on-call rotations, incident response practices, SLO definitions, and reliability engineering as first-class team responsibilities, not afterthoughts Build a team culture where AI-assisted development is the default and delivery friction is identified and eliminated aggressively — ensuring the team ships to production constantly and that process or tooling obstacles are treated as urgent engineering problems Partner closely with TR Labs to ensure that new retrieval techniques, embedding models, re-ranking approaches, and agentic search patterns have a clear, well-supported path from prototype to production within the platform’s architecture — including the infrastructure required to serve custom models in production with appropriate latency SLOs, versioning, and rollback capability Oversee platform infrastructure including event streaming (Kafka/MSK), cloud services (AWS), observability tooling, and security controls including multi-tenant data isolation and customer-controlled encryption Build and lead a team of approximately 10 software engineers (including Staff and Senior levels), managing hiring, onboarding, performance, and professional development with a focus on cultivating deep technical ownership Develop engineers who bring together distributed systems depth, search domain expertise, and a strong sense of operational responsibility — engineers who own their work from the first line of code to the production dashboard Foster a culture of empowered ownership — where engineers have the autonomy to define the problem, the authority to push back on poor technical decisions, and the accountability to carry work from design through production operations Translate complex platform and search concepts to non-technical stakeholders — making the value and trade-offs of platform investments legible to product managers and business leaders Balance the team’s platform engineering responsibilities with direct search solution delivery for CoCounsel’s highest-priority use cases Define and maintain engineering processes for a team that both builds shared platform infrastructure and delivers production search solutions — ensuring rigorous testing, code review, reliability standards, and continuous evaluation of search quality through both offline grading pipelines and online signals such as query performance monitoring, A/B experiments, and engagement analytics Establish platform health and developer-experience benchmarks — including API reliability SLOs, client onboarding time-to-value, and search quality metrics — and use them to drive continuous improvement Evaluate and integrate emerging technologies — search engines, vector databases, streaming frameworks, AI development tooling, agentic retrieval patterns, orchestration tools — with a clear-eyed assessment of production-readiness and operational implications Cultivate a strong, productive partnership with TR Labs — engaging early in the research and experimentation lifecycle to shape platform requirements, co-develop integration patterns, and ensure that promising AI capabilities have a clear and well-supported path to production Collaborate closely with product management, TR Labs, and consuming engineering teams to align the platform roadmap with business priorities across CoCounsel, Westlaw, and the broader TR product portfolio About You You’re an ideal fit if you have: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field 8+ years of software engineering experience, with at least 3 years in a technical leadership or engineering management role Demonstrated experience designing and operating large-scale distributed data systems — event streaming, data pipelines, or search/indexing infrastructure — at production scale Strong platform and systems thinking: a track record of building shared infrastructure consumed by multiple teams, with a product mindset toward developer experience and internal customer satisfaction Experience leading teams that own their production systems end-to-end — including on-call responsibilities, SLO management, and incident response — with a clear philosophy that building and operating are inseparable Proven ability to build high-velocity engineering teams: reducing delivery friction, enabling constant production deployments, and embedding AI-assisted development practices as a team norm Advanced knowledge of distributed systems design, cloud infrastructure (AWS preferred), API design, and software architecture Proficiency in Python and strong software engineering fundamentals, including DevOps practices and observability Familiarity with information retrieval, search systems, or vector/hybrid search concepts sufficient to make sound architectural decisions and partner effectively with search engineers and research scientists Awareness of AI ethics, governance, and responsible technology deployment Strong leadership skills: proficiency in agile methodologies, excellent communication, and the ability to build alignment across engineering, product, and science teams Hands-on experience with search engines such as Vespa, OpenSearch, Elasticsearch, or Solr Experience building multi-tenant platform infrastructure with strong data isolation, customer-managed encryption, or other enterprise security requirements Background in event-driven architectures and stream processing frameworks (Kafka, MSK, or similar) Experience partnering with AI/ML research teams to operationalize retrieval models, embedding pipelines, or re-ranking systems Develop a thorough understanding of the platform’s current architecture, technical debt, team composition, and the most pressing gaps in reliability, developer experience, and delivery velocity Estab