{"schemaVersion":"jobsearcher.job.v1","id":"f20579a0333e4fc6c8d135f4","url":"https://jobsearcher.com/jobs/f20579a0333e4fc6c8d135f4","canonicalUrl":"https://jobsearcher.com/jobs/f20579a0333e4fc6c8d135f4","title":"Senior/Lead Fullstack Developer","description":"A World Changing Mission\nPolysentry’s leading data analytics and intelligence solutions empower teams to swiftly convert vast amounts of global data into actionable and contextual insights, enabling organizations to make better decisions.\nWe engage in close collaboration with customers in high-stakes industries, including financial services, legal, and government. The vital insights we deliver play a pivotal role in safeguarding critical assets on a global scale.\n‍\nOur Company\nPolysentry is a technology company that provides industry leading data discovery, classification and analysis solutions. Since 2018, Polysentry has been building and deploying mission-ready AI-based platforms that meet rapidly evolving security needs. The company’s software solutions are built for corporate and government organizations.\n‍\nOur Team\nOur innovative team is building cutting-edge Retrieval-Augmented Generation (RAG) systems that significantly improve information retrieval accuracy. We're working with the latest embedding models, vector databases, and LLMs to develop solutions that maintain critical context during retrieval operations.\n‍\nThe Role\nWe're looking for a Senior Engineer to help us build and optimize our advanced RAG platform. Your work will enable customers to unlock new levels of performance from their knowledge bases across various domains.\n‍\nResponsibilities\nImplement and optimize contextual embedding and preprocessing pipelines\nDesign efficient document chunking and context generation workflows\nBuild reranking systems that further improve retrieval accuracy\nDevelop evaluation frameworks to measure retrieval performance across different domains\nCreate cost-effective solutions using prompt caching and other optimization techniques\nExperiment with different embedding models to identify optimal configurations\n‍\nRequirements\nExperience with embedding models (Gemini, Voyage, or similar)\nStrong understanding of vector databases and similarity search\nExperience with prompt engineering for context generation\nFamiliarity with document chunking strategies and preprocessing\nUnderstanding of reranking systems and their implementation\nBackground in measuring retrieval accuracy (recall metrics)\nProgramming experience in Python or similar language\nExperience with large-scale data processing\n‍\nNice to Have\nBackground in NLP, information retrieval, or computational linguistics\nExperience with RAG system architecture and implementation\nKnowledge of LLM prompt caching and optimization techniques\nFamiliarity with domain-specific retrieval challenges (code, scientific papers, etc.)\nExperience balancing performance improvements against latency and cost considerations\nBackground in developing or working with major enterprise LLMs\nUnderstanding of AWS or similar cloud infrastructure for LLM applications\n‍ ‍\nTHINK YOU ARE A GOOD FIT? SUBMIT YOUR RESUME FOR THE POSITION TODAY! CONTACT@POLYSENTRY.COM","company":"Polysentry","rawCompany":"polysentry","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-09T14:24:12.786Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1254.00","title":"Web Developers","slug":"web-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Senior/Lead Fullstack Developer","description":"A World Changing Mission\nPolysentry’s leading data analytics and intelligence solutions empower teams to swiftly convert vast amounts of global data into actionable and contextual insights, enabling organizations to make better decisions.\nWe engage in close collaboration with customers in high-stakes industries, including financial services, legal, and government. The vital insights we deliver play a pivotal role in safeguarding critical assets on a global scale.\n‍\nOur Company\nPolysentry is a technology company that provides industry leading data discovery, classification and analysis solutions. Since 2018, Polysentry has been building and deploying mission-ready AI-based platforms that meet rapidly evolving security needs. The company’s software solutions are built for corporate and government organizations.\n‍\nOur Team\nOur innovative team is building cutting-edge Retrieval-Augmented Generation (RAG) systems that significantly improve information retrieval accuracy. We're working with the latest embedding models, vector databases, and LLMs to develop solutions that maintain critical context during retrieval operations.\n‍\nThe Role\nWe're looking for a Senior Engineer to help us build and optimize our advanced RAG platform. Your work will enable customers to unlock new levels of performance from their knowledge bases across various domains.\n‍\nResponsibilities\nImplement and optimize contextual embedding and preprocessing pipelines\nDesign efficient document chunking and context generation workflows\nBuild reranking systems that further improve retrieval accuracy\nDevelop evaluation frameworks to measure retrieval performance across different domains\nCreate cost-effective solutions using prompt caching and other optimization techniques\nExperiment with different embedding models to identify optimal configurations\n‍\nRequirements\nExperience with embedding models (Gemini, Voyage, or similar)\nStrong understanding of vector databases and similarity search\nExperience with prompt engineering for context generation\nFamiliarity with document chunking strategies and preprocessing\nUnderstanding of reranking systems and their implementation\nBackground in measuring retrieval accuracy (recall metrics)\nProgramming experience in Python or similar language\nExperience with large-scale data processing\n‍\nNice to Have\nBackground in NLP, information retrieval, or computational linguistics\nExperience with RAG system architecture and implementation\nKnowledge of LLM prompt caching and optimization techniques\nFamiliarity with domain-specific retrieval challenges (code, scientific papers, etc.)\nExperience balancing performance improvements against latency and cost considerations\nBackground in developing or working with major enterprise LLMs\nUnderstanding of AWS or similar cloud infrastructure for LLM applications\n‍ ‍\nTHINK YOU ARE A GOOD FIT? SUBMIT YOUR RESUME FOR THE POSITION TODAY! CONTACT@POLYSENTRY.COM","datePosted":"2026-08-09T14:24:12.786Z","dateModified":"2026-08-09T14:24:12.786Z","hiringOrganization":{"@type":"Organization","name":"Polysentry","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"f20579a0333e4fc6c8d135f4"},"url":"https://jobsearcher.com/jobs/f20579a0333e4fc6c8d135f4"}}