> Markdown version of [/jobs/ext/3098008-software-engineer-iv-search-platform](https://www.wearedevelopers.com/jobs/ext/3098008-software-engineer-iv-search-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer IV - Search Platform - **Company:** GRAINGER, INC. - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $134,100.0 - $223,500.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Data Analysis, Code Review, Computer Programming, Continuous Delivery, Shard (Database Architecture), DevOps, Distributed Systems, IT Management, Routing, Pair Programming, Scrum Methodology, Search Technologies, Software Engineering, Large Language Models, Caching, Indexer, Information Technology, Low Latency, Physical Design - **Published:** September 26, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18447785?backUrl=%2Fcareer%2F18447785%2FSoftware-Engineer-Iv-Search-Platform-Illinois-Chicago ## About the Role * Bachelor's Degree or equivalent experience in computer science or similar; or equivalent experience required * 5+ years experience as a Software Engineer; with experience in modern software engineering; designing; devloping, testing and deploying scalable software applications within a variety of technologies and environments. * Expert knowledge of programming skills, including Java and Python * Demonstrated knowledge of distributed system design and integration patterns, , including sharding, replication, indexing, query routing, and caching in distributed search platforms * Familiarity with Agile/Scrum methodologies and Dev Ops Practices, and AI-assisted development tools * Experience with analyzing, interpreting and communicating complex problems and practices * Hands-on experience with embeddings and vector search, including ANN indexing and the practical tradeoffs between relevance, latency, and cost * Experience tuning search and AI-based customer experiences, using user behavior and measured outcomes to decide what to change ## Description As a Lead Software Engineer (Software Engineer IV) you will develop applications that align with a strategic vision. In addition to coaching engineers, you will partner with key stakeholders including Product Managers and Architecture. You will embrace curiosity to ensure a deep understanding of the business requirements that drive the analysis and physical design of technical solutions. In this role you will focus on search relevance for Grainger's product catalog, the systems that determine which products a customer sees when they search. You will work across both lexical and semantic retrieval, partnering with Data Science on embedding models and with Product and Analytics on how relevance is measured. Search quality at this scale is measured rather than assumed, so experiment design and analysis are a core part of the role alongside engineering. You Will * Lead engineer on a team responsible for the application and delivery of high-quality, maintainable software for highly complex applications * Influence team adoption of sensible defaults to enable continuous delivery activities * Contribute to continuous learning on your team culture by leading knowledge sharing sessions with latest technological features and engineering practices * Maintain software in production with demonstrated ability to triage and resolve issues * Mentor developers, conduct code reviews, and participate in pair programming * Partners directly with IT Management team to ensure successful design and delivery of technology based solutions * Design, build, and improve search systems using lexical (e.g., BM25/TF-IDF) and semantic/vector-based retrieval approaches. * Develop and optimize ranking strategies, including hybrid retrieval, reranking, and learning-to-rank techniques to improve relevance. * Evaluate search quality using offline metrics (e.g., NDCG, MRR, Precision/Recall) and online experiments, and build tooling that makes relevance experiments repeatable and measurable.