01Overview
GenAI / LLM Application EngineerRole Summary :We are looking for a GenAI / LLM Application Engineer to build production-grade AI assistants, retrieval systems, and workflow automation solutions. The role requires hands-on experience with multi-agent orchestration, RAG pipelines, search and retrieval infrastructure, backend APIs, and user-facing chatbot experiences.The ideal candidate can take a business workflow, break it into AI-enabled subtasks, connect the right tools and services, and deliver reliable, measurable outcomes.Key Responsibilities :- Design and implement multi-agent orchestration systems that can decompose complex user requests into smaller tasks.- Build retrieval-augmented generation pipelines for enterprise documents and knowledge bases.- Develop and optimize search flows using vector search, semantic search, keyword search, and hybrid retrieval.- Integrate LLMs with external tools, APIs, and enterprise systems such as ticketing, HR, or support platforms.- Create backend services using Python and FastAPI to power AI features and APIs.- Work with LangChain and LangGraph to implement agent workflows, tool calling, and retrieval logic.- Build and maintain chatbot interfaces using React, Chainlit, or similar frontend frameworks.- Manage token limits, prompt quality, context handling, and conversation history strategies.- Evaluate response quality using human review, recall vs precision analysis, and automated evaluation methods.- Collaborate with product, backend, and business teams to translate workflows into AI solutions.Required Skills :- Strong experience in Python backend development.- Hands-on experience with FastAPI or similar API frameworks.- Practical knowledge of LangChain and/or LangGraph.- Experience building RAG systems with chunking, embeddings, retrieval, and prompt assembly.- Familiarity with Elasticsearch or other vector/search databases.- Understanding of embeddings, transformers, attention, tokenization, and generation settings such as temperature, top-p, and top-k.- Ability to design prompt and context management strategies for longer conversations.- Experience integrating third-party APIs and enterprise tools.- Strong problem-solving ability and production-oriented engineering mindset.Preferred Skills :- Experience with MCP and tool-based agent architectures.- Knowledge of reranking, hybrid search, BM25, and HNSW.- Experience with Azure AI Search, Azure OpenAI, blob storage, or other Azure services.- Experience with React or Chainlit for AI chatbot interfaces.- Exposure to automated evaluation frameworks such as Ragas.- Familiarity with distributed systems, event-driven workflows, or microservices.Qualifications :- 5+ years of software engineering experience, with at least part of that focused on AI or backend development.- Proven ability to ship features end to end, from backend logic to user-facing experience.- Experience working in production environments with measurable performance or quality outcomes. (ref:hirist.tech) .
