We are looking for a Lead Software Engineer, Search to pioneer the next evolution of our search infrastructure. In this role, you won't just be maintaining query pipelines; you will be responsible for building, iterating, and scaling semantic search via hybrid search on OpenSearch as a core, foundational platform capability. As the technical lead for this initiative, you will architect the systems that blend traditional keyword matching with deep semantic understanding. You will own the strategy for integrating vector embeddings, neural search, and dense/sparse hybrid retrieval, directly impacting how users discover data across our entire ecosystem. If you are a hands-on technical leader who loves OpenSearch, relevancy tuning, and building high-throughput, foundational capabilities, we want you in our Austin hub. What You'll Do • Architect the Future of Search: Lead the design and implementation of semantic search capabilities, utilizing OpenSearch to build a robust, hybrid search (BM25 + vector) capability from the ground up • Iterate & Optimize: Continuously evaluate, benchmark, and fine-tune search relevance, ranking models, and k-NN/neural search configurations within OpenSearch • Own the Indexing Pipeline: Maintain, scale, and evolve our core data ingestion and indexing pipelines (built on MySQL, Kafka/RabbitMQ, and backend microservices) to seamlessly support dense vector ingestion and de-duplicated, resilient synchronization • Technical Leadership: Guide the technical roadmap for the Search team, establish engineering best practices, and mentor senior and mid-level engineers through complex architectural decisions • Production Excellence: Ensure the search platform meets ultra-low latency requirements and high-availability SLAs under massive, concurrent traffic loads while participating in the team's on-call rotation Who Are You • Experience: 7+ years of professional software development experience, with a proven track record in a technical leadership or staff-level capacity • OpenSearch/Elasticsearch Expertise: Deep hands-on experience building, scaling, and fine-tuning OpenSearch (or Elasticsearch) clusters at scale • Semantic & Hybrid Search: Proven experience implementing semantic search, working with text embeddings, vector databases, and configuring hybrid search scoring models • Strong Backend Fundamentals: High proficiency in a strongly typed language like GoLang, Scala, or Java, alongside experience with languages like PHP • Data Pipelines: Strong experience with relational databases (MySQL), schema design, and distributed messaging tools (Kafka or RabbitMQ) for heavy data mutation and indexing • Location: Must be based in or willing to relocate to the Austin, TX area and comfortable working in a hybrid environment • Familiarity with the OpenSearch Neural Search plugin, k-NN search, or Learning to Rank (LTR) • Experience migrating large-scale search infrastructure from traditional Elasticsearch configurations to advanced OpenSearch semantic implementations • Experience setting up automated search quality measurement frameworks (e.g., NDCG, MRR) • Familiarity with containerization and orchestration (Docker, Kubernetes) in a cloud environment Work Where You Thrive For candidates based in the Austin metro area the position follows a hybrid work model with three days per week in the office, balancing focused individual work with meaningful in-person collaboration. #LI-REMOTE #LI-GC1 (Pay Transparency Range: $163,000.00 - $244,000.00) Compensation Transparency The national base salary range for this role is posted above in this job post. Final compensation will be determined based on factors such as relevant experience, skills, qualifications and geographic location. We also consider internal equity to help ensure fair and consistent pay practices across our teams. Where applicable, this role may also be eligible for variable compensation (such as bonus or commission), equity, and benefits in accordance with local policies. Details will be shared during the hiring process. We are committed to equitable and transparent pay practices that align to market data, internal equity, and individual contribution.