Lead Retrieval Engineer: AI-Driven Search & OpenSearch

Thomson Reuters; Ann Arbor (MI); Hybrid; USD 137,000 - 255,000; Full time

Benefits offered by this job

Hybrid Work Model

Competitive Benefits

Career Growth

Job summary

Thomson Reuters is seeking a research engineer lead in the United States to own end-to-end delivery of large-scale search and retrieval projects within TR Labs. You will partner with applied scientists, implement production-grade retrieval architectures, and ship reusable components for agentic AI workflows.

This role emphasizes evidence-driven design, experimentation, and cross-team leadership. The candidate should have deep experience in production search systems, Python engineering, and AWS,

Qualifications

• 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 owned.
• Proven track record leading technical projects and delivering through other engineers
• Deep hands-on production expertise in OpenSearch or Vespa (or comparable depth in Elasticsearch, Solr, or Lucene)
• Rigor with evidence: designing search experiments, relevance and ranking metrics, offline evaluation harnesses, online A/B measurement
• 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
• Designing, operating, and scaling production APIs and large-scale distributed systems on AWS
• Information retrieval fundamentals: indexing/ingestion at large corpus scale, vector search, embeddings, semantic and hybrid retrieval, and RAG infrastructure

Responsibilities

• 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
• Run the exploration POC proof of value productionization loop, and decide what to try next, including what not to try
• 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
• 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
• Influence architecture decisions beyond your own squad through design review, alignment with partner teams, and mentorship.

Skills

Technical leadership

Search/retrieval systems

Python production engineering

AWS production APIs

OpenSearch/Vespa

AI-native development

Cross-team collaboration

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

OpenSearch

Vespa

Elasticsearch

Solr

Lucene

Python

AWS

Job description

Thomson Reuters is seeking a research engineer lead in the United States to own end-to-end delivery of large-scale search and retrieval projects within TR Labs. You will partner with applied scientists, implement production-grade retrieval architectures, and ship reusable components for agentic AI workflows.

This role emphasizes evidence-driven design, experimentation, and cross-team leadership. The candidate should have deep experience in production search systems, Python engineering, and AWS,