{"id":2776424,"url":"https://alion.io/job/swits-digital-private-limited-ai-engineer","title":"AI Engineer","company":{"id":4442893,"name":"Swits Digital Private Limited","domain":"switsdigital.com","url":"https://alion.io/company/swits-digital-private-limited","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, 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management\nCustom tools and tool integration\nMemory management\nHuman-in-the-loop workflows\nIntegrate and work with LLM APIs, including OpenAI, Anthropic, and Azure OpenAI.\nImplement function/tool calling and structured output to build reliable LLM-powered applications.\nDevelop end-to-end Retrieval-Augmented Generation (RAG) solutions, including:\nData ingestion and preprocessing\nEmbedding generation\nVector database/search implementation\nRetrieval optimization and quality tuning\nWork with both SQL and NoSQL databases, designing and modelling data structures to support application and AI/retrieval use cases.\nDevelop and maintain functional front-end interfaces using React and TypeScript, with the ability to independently build and enhance user-facing features.\nContainerize applications using Docker and follow best practices for source control and collaborative development using Git.\nImplement and maintain CI/CD pipelines and support application deployment across cloud environments.\nCollaborate with cross-functional teams to design, develop, test, deploy, and continuously improve AI-powered software solutions.\n Required Skills\n\nPython 4+ years of production experience\nFastAPI / equivalent backend frameworks\nAsync programming and API development\nLangChain and LangGraph\nLLM APIs OpenAI / Anthropic / Azure OpenAI\nFunction calling / Tool calling / Structured output\nRAG and vector search\nEmbeddings and retrieval optimization\nSQL & NoSQL databases\nReact & TypeScript\nDocker & Git\nCI/CD\nCloud deployment\n\nPreferred Profile\n\nCandidates should have strong hands-on software engineering experience combined with practical GenAI/LLM application development experience, particularly with LangChain, LangGraph, RAG, LLM APIs, and production Python 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