# Staff Software Engineer, Search Retrieval Platform

**Company**: Thomson Reuters
**Location**: United States of America, New York, New York
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $136,000 USD - $253,000 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://thomsonreuters.wd5.myworkdayjobs.com/en-US/External_Career_Site/job/United-States-of-America-New-York-New-York/Staff-Software-Engineer--Search-Retrieval-Platform-_JREQ205148?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/staff-software-engineer-search-retrieval-platform-6d529cf9-fd9/

## Description

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

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## Skills

### Required
- Python
- Java
- Go
- distributed systems
- API design
- search engines
- retrieval platforms
- AI-assisted development

### Nice to have
- Vespa
- OpenSearch
- Elasticsearch
- hybrid retrieval
- ranking
- embedding pipelines
- AI agents
- search evaluation
- multi-tenant authentication

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