About the company
Our partner is looking for a Staff Backend Engineer, Search based in the United States.
Responsibilities
- Design, implement, and evolve robust backend search solutions capable of scaling with a rapidly growing user base.
- Architect and optimize search infrastructure built on technologies such as OpenSearch, Elasticsearch, and Postgres.
- Improve search relevance, accuracy, latency, and overall result quality to help users quickly find the information they need.
- Build and optimize real-time indexing and ingestion pipelines so search results remain current and reliable.
- Develop measurement and evaluation frameworks that provide actionable insight into search quality and guide continuous improvement.
- Build and enhance vector search capabilities, including semantic search and embedding-based experiences, to support next-generation AI-powered functionality.
- Optimize query parsing, indexing strategies, relevance tuning, and search-serving performance across high-scale environments.
- Collaborate with AI, backend engineering, and product teams to integrate search capabilities into new features and workflows.
- Investigate and resolve complex search-related production issues, ensuring reliability and performance under demanding workloads.
- Provide technical leadership on search architecture, engineering decisions, and scalable solutions that maintain performance as usage grows.
- Contribute to the evolution of search technology and help establish engineering practices that improve maintainability, observability, and operational excellence.
Requirements
- Bachelor’s degree in Computer Science or a related technical field.
- 7+ years of professional experience as a search engineer or in a closely related backend engineering role.
- Strong hands-on production experience with OpenSearch or Elasticsearch; experience with Solr may also be considered.
- Proven experience designing and operating high-scale, real-time data ingestion and search-serving systems within backend service environments.
- Strong understanding of query parsing, indexing, relevance tuning, search optimization, and information retrieval concepts.
- Demonstrated experience measuring, evaluating, and improving search quality using data-driven approaches.
- Experience designing search architectures that maintain strong performance and reliability under heavy workloads.
- Strong software engineering and problem-solving abilities, with the capacity to troubleshoot complex distributed search systems.
- Experience collaborating effectively with backend engineers, AI/ML specialists, product managers, and other cross-functional stakeholders.
- Familiarity with search ranking, relevance algorithms, and information retrieval is highly desirable.
- Hands-on experience with vector embeddings and semantic search implementations is preferred.
- Experience applying machine learning or natural language processing techniques to improve search relevance is a plus.
- Experience with TypeScript in backend systems is desirable.
- Ability to operate at a high technical level while contributing to architectural direction and long-term search strategy.
Conditions
- Estimated base compensation of $250,000–$300,000 USD, with actual compensation determined by factors including location, experience, education, skills, and interview performance.
- Equity opportunities.
- 401(k) plan.
- Health, dental, and vision insurance.
- Flexible spending and other spending accounts.
- Life and disability insurance coverage.
- Paid parental leave.
- Flexible paid time off.
- Enhanced employee assistance program.
- Employee wellness stipend.
- Professional development stipend.
- Opportunity to work on AI-native products and advanced search technologies.
- Collaborative environment with opportunities to work across backend engineering, AI, and product teams.