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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) .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.