Senior Software Engineer, Search Platform

Senior Software Engineer, Search Platform Our vision

We are building the next-generation search platform, with a vision to democratize knowledge construction and consumption at Thomson Reuters. The platform consolidates search systems across Thomson Reuters products and services, serving millions of end users, internal agents, and internal search teams, into a fully managed, customizable, sovereign, and self-serve search platform.

Job Description The AI Enabled Software Engineering (AIESE) team within Thomson Reuters is seeking Senior Software Engineers to build the core of that platform: the ingestion pipelines that turn content into searchable knowledge, the APIs that serve it to products and AI agents, and the cloud infrastructure that keeps it fast and reliable. Your work is what lets internal teams create, configure, and run search on their own, without waiting on a central team.

This is a full-ownership role. You design, build, test, deploy, and operate production systems  ship to production constantly, treat delivery friction as an engineering problem to solve, and use AI-assisted development as a primary tool. Senior Engineers here hold design authority within their scope, share expertise across the team, and mentor more junior engineers.

Key Responsibilities:

Build the platform

Design, build, and test platform services across document ingestion, search indexing, and query APIs, using the language best suited to the problem (for example Python, Java, or Go).Build reliable pipeline components that move documents through parsing, chunking, enrichment, and indexing, using proven patterns for retries, dead-letter queues, and idempotent processing.

Build self-service platform APIs that let client teams configure search systems, manage index life cycles, and monitor ingestion health.

Design retrieval interfaces for products and AI agents with predictable contracts, explicit latency budgets, and result payloads sized for LLM context windows.

Contribute to the move from Open Search to Vespa, including schema migrations and zero-downtime index promotion.

Instrument retrieval components so offline evaluation and LLM-as-judge grading can compare pipeline versions and measure search quality.

Operate what you build

Take part in the on-call rotation and own incidents in your scope, from triage and root cause to post-mortem and systemic fixes.

Add logging, metrics, and distributed tracing to your components, including trace-level visibility into agentic retrieval paths, and help define SLOs.Remove delivery friction wherever you find it: slow deployments, flaky tests, and painful local workflows. Use AI-assisted tools fluently and share what works.

Lead and collaborate

Take technical direction for assigned projects, break customer and product requirements into executable work, and mentor more junior engineers through review and pairing.

Work with TR Labs and research scientists to bring new search capabilities, such as embedding models, chunking strategies, and re-ranking, into production in a well-tested and observable way.

Work with client teams to understand how they use the platform and turn their feedback into platform improvements.

Required Qualifications:

5+ years of software engineering experience building and operating production backend or data infrastructure systems, with end-to-end ownership of features and components. A degree in Computer Science, Engineering, or a related field, or equivalent experience

Strong programming skills in at least one of Python, Java, Go, or an equivalent language, and the judgment to choose the right tool for the job Solid distributed systems fundamentals: you understand how queues, streaming pipelines, and distributed data stores fail, and you design for it Hands-on experience with a major cloud platform (AWS preferred) and infrastructure as code Operational ownership: on-call, incident response, and observability, with the view that building and operating are inseparable

Fluency with AI-assisted development tools and clear communication with technical and non-technical stakeholders

Preferred qualifications:

Production experience with a search engine such as Open Search, Elasticsearch, Vespa, or Solr, including writing queries, designing indexes, or operating clusters

Experience with Kafka or another event streaming platform

Experience integrating AI services, such as embedding, re-ranking, and RAG components, with sound error handling and fallbacks

Exposure to agentic retrieval patterns, such as multi-hop…