Staff Software Engineer, Search Retrieval Platform

Thomson Reuters · United States of America, New York, New York · $136,000 USD - $253,000 USD · hybrid We are building the next-generation search platform at Thomson Reuters, with a vision to democratize knowledge construction and consumption. The platform consolidates search systems across products and services, serving millions of end users. As a Staff Software Engineer, you will build platform capabilities that let any product team, research team, or AI agent get high-quality, customizable search without building it from scratch. You will work closely with product, research engineering, and applied science partners. Key Responsibilities: Turn customer and product needs into platform capabilities Design retrieval APIs and search services for end users, AI agents, and internal systems Make retrieval customizable by design with pluggable components Own content ingestion and indexing on the platform Partner across disciplines: Partner with Research Engineering and Applied Science to take new retrieval techniques from experiment to supported platform capability Work with product and client teams to prioritize the roadmap and bring adoption feedback back into the platform Quality, security, and trust: Build evaluation into the platform with offline evaluation, search grading, and online experiments Own the security posture of retrieval with multi-tenant data isolation and entitlements enforced at query time Own SLOs, observability, and on-call for what you build Technical leadership: Set architectural direction and design patterns across retrieval and search services Lead cross-team initiatives and make hard trade-offs between near-term product needs and long-term platform goals Mentor Senior and mid-level engineers Required Qualifications: 8+ years of software engineering experience with progression to staff-level scope Experience building search, retrieval, or data-intensive platforms at scale Track record translating customer needs into platform capabilities Experience designing APIs and services consumed by multiple teams Operational rigor with SLOs, observability, on-call ownership, and learning from incidents Fluency with AI-assisted development tools Preferred qualifications: Production experience with search engines such as Vespa, OpenSearch, or Elasticsearch Experience with hybrid retrieval, ranking, and embedding pipelines Experience building tools or APIs for AI agents Search evaluation experience Multi-tenant authentication, authorization, and entitlements Experience operationalizing ML models in production What Success Looks Like: In the first 90 days: Learn the platform's retrieval, indexing, and API architecture; build relationships with product, research, and client teams; take on-call ownership and deliver one meaningful improvement In the first year: Deliver a customizable retrieval capability; establish evaluation coverage, SLOs, and runbooks; move at least one research innovation from experiment to supported platform capability What's in it For You: Hybrid Work Model Flexibility & Work-Life Balance Career Development and Growth Industry Competitive Benefits Culture Social Impact