Senior AI Engineer LLM RAG amp Agent SystemsAbout the RoleWe are looking for a Senior AI Engineer to own the AI layer of our data platformbuilding productiongrade LLM applications retrieval systems intelligent agents and naturallanguage interfaces over enterprise dataYou will work across RAG embeddings vector and hybrid search agenttoolcalling architectures LLM evaluation and selfhosted openweight modelsThis is a handson engineering role for someone who has moved beyond prototypes and has built deployed and operated LLM systems in productionWhat Youll OwnDesign and build productiongrade LLM applications and RAG systemsOwn retrieval architecture including chunking embeddings vector search hybrid search and rerankingBuild agentic and toolcalling systems with appropriate permissions scoping validation and guardrailsDevelop naturallanguage interfaces over enterprise data and structured databasesBuild and maintain LLM evaluation frameworks including test sets regression suites grounding hallucination and answerquality evaluationWork within our data platform and engineering stack rather than relying solely on hosted AI APIsDeploy and optimize selfhosted openweight models using technologies such as vLLM or equivalent serving infrastructureOptimize inference performance GPU utilization latency throughput and costExplore and implement finetuning or model adaptation when appropriateCollaborate with data and software engineers to turn AI capabilities into reliable production productsRequired Qualifications5 years of software or data engineering experienceAt least 2 years of handson experience building and deploying production LLMbased systemsStrong Python engineering skillsDeep understanding of RAG and retrieval architectureChunking strategiesEmbeddingsVector databasessearchHybrid searchRerankingRetrieval evaluationExperience building LLM agents or toolcalling systemsUnderstanding of permissions access control scoping validation and guardrails for AI systemsStrong understanding of LLM evaluation including test datasets regression testing grounding and hallucination detectionExperience working directly with data platforms databases or enterprise data rather than only consuming hosted LLM APIsStrong software engineering fundamentals and experience taking systems from prototype to productionStrongly PreferredExperience with selfhosted openweight modelsProduction experience with vLLM or equivalent modelserving infrastructureUnderstanding of GPU resource management and inference optimizationExperience with finetuning LoRA or other modeladaptation techniquesExperience with TexttoSQL systemsExperience designing or using a semantic layer over real enterprise data modelsExperience combining unstructured documents with structured enterprise data in a single AI applicationWhat Success Looks LikeYou will be successful in this role if you can build an AI layer that isAccurate answers are grounded in enterprise dataReliable quality is measured through automated evaluation and regression testingSecure agents and tools respect user permissions and data boundariesScalable models and retrieval infrastructure perform reliably in productionMaintainable AI capabilities are built as production software not isolated experimentsUseful users can interact naturally with complex enterprise data
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