Infosys - AI Engineer - LLM/RAG in Bengaluru, India - Jobeax
Vacancy description
Infosys - AI Engineer - LLM/RAG in Bengaluru, India
India, Bengaluru
Infosys - AI Engineer - LLM/RAG in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
About the Role : We are looking for a highly experienced AI Engineer to design, develop, and deploy enterprise-grade AI and Generative AI solutions. The role requires strong hands-on engineering expertise along with the ability to lead complex AI initiatives and guide engineering https://jobeax.com/link/ZlR3JZToBtLJKlA9 Responsibilities : - Design, develop, and deploy production-grade AI/ML solutions.- Develop Generative AI applications using LLMs and modern AI frameworks.- Build RAG-based applications using enterprise data and knowledge sources.- Develop AI agents and agentic workflows for complex enterprise use cases.- Implement model inference, evaluation, optimization, and monitoring pipelines.- Integrate AI models with enterprise applications through APIs and microservices.- Develop NLP, machine learning, and deep learning solutions based on business requirements.- Work with structured and unstructured data for AI applications.- Build prompt engineering, model evaluation, grounding, and retrieval strategies.- Implement vector search, embeddings, semantic search, and knowledge retrieval.- Deploy AI models and applications in scalable production environments.- Optimize model performance, latency, scalability, and infrastructure utilization.- Implement AI application security, governance, monitoring, and observability.- Conduct technical POCs and evaluate new AI models and frameworks.- Collaborate with data engineers, software engineers, architects, and product teams.- Mentor senior engineers and establish engineering best practices.- Troubleshoot complex technical issues across AI applications and https://jobeax.com/link/pNYMYAcVgoA9do1S Skills : - 10-12 years of experience in software engineering, AI/ML engineering, or related technology roles.- Strong proficiency in Python.- Extensive experience with Machine Learning, Deep Learning, NLP, and Generative AI.- Strong hands-on experience with LLMs and LLM-based applications.- Experience with RAG, embeddings, vector databases, prompt engineering, and AI agents.- Experience with AI/ML frameworks and model development libraries.- Strong software engineering fundamentals including APIs, microservices, databases, and distributed systems.- Experience deploying AI solutions into production environments.- Strong understanding of MLOps, model lifecycle, monitoring, and evaluation.- Experience working with cloud-based AI/ML environments.- Strong debugging, architecture, problem-solving, and technical leadership capabilities. (ref:hirist.tech)
... AI / Generative AI Engineer with 6+ years of experience in building and deploying AI-powered applications. The role focuses on developing practical Generative AI solutions using LLMs, RAG, Agentic AI frameworks, and cloud-based AI https://jobeax.com/link/tlplQAnK5B36KMXq Responsibilities :- Develop and deploy AI-powered ...
... focus on quality KPIs Detail-oriented with a strong bias toward automation and scalability Experience Requirements - 7+ years in QA, SDET, or test automation engineering - Proven experience building and scaling automation frameworks - Hands-on experience with AI/ML systems or LLM-based applications Experience testing RAG ...
... NLP, RAG, and AI agents.- Develop scalable ML/AI pipelines for training, evaluation, deployment, inference, monitoring, and retraining.- Own key aspects of MLOps/LLMOps, including CI/CD, automated testing, model/prompt versioning, deployment, monitoring, and lifecycle management.- Build LLM evaluation and observability capabilities ...
... ideally including Azure AI Foundry, Azure OpenAI Service, and Azure Data Lake - Breadth across ML domains: traditional/statistical ML, deep learning, NLP, and LLM/GenAI applications, including hands-on experience with prompt engineering, RAG, embeddings, and agentic workflows - Practical experience building LLM/GenAI applications ...
... Responsibilities :- Build and deploy enterprise-scale GenAI applications, copilots, and AI assistants.- Develop RAG pipelines, vector search solutions, and agentic AI workflows.- Integrate and optimize LLMs using AWS Bedrock and Azure OpenAI.- Create scalable APIs and cloud-native AI services on AWS.- Improve AI accuracy, retrieval ...
... Generative AI Engineer certification.- Microsoft Certified: Azure AI Engineer Associate (AI - 102).- Demonstrated experience optimizing inference pipelines (vLLM, Ollama, TensorRT - LLM) or implementing Graph - based https://jobeax.com/link/ClcwQg3Xe0Yg5wLt We Offer :- Work on high - impact GenAI customer deployments across ...
... Generative AI Engineer certification.- Microsoft Certified: Azure AI Engineer Associate (AI - 102).- Demonstrated experience optimizing inference pipelines (vLLM, Ollama, TensorRT - LLM) or implementing Graph - based https://jobeax.com/link/ClcwQg3Xe0Yg5wLt We Offer :- Work on high - impact GenAI customer deployments across ...
... architect robust, scalable, and secure AI systems leveraging Generative AI, Large Language Models (LLMs), Agentic AI, and advanced Machine Learning while mentoring engineering teams and driving technical https://jobeax.com/link/n7v7vfl76y3kLxkA Responsibilities :- Architect and develop scalable AI/ML solutions.- Build production-grade ...
... Interested in shaping the future of healthcare with AI Explore opportunities at https://jobeax.com/link/l2ilzLBJSLK6rA75 and drive innovation with #YouToThePowerOfAI. The AI Engineer is an ML engineer responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ...
... Azure OpenAI- Strong experience with LangGraph, LangChain, AutoGen or CrewAI- Strong Python, FastAPI and asynchronous programming skills- Hands-on experience with RAG pipelines and Vector Databases such as FAISS, Pinecone or pgvector- Experience with Prompt Engineering and LLM evaluations- Strong understanding of Agentic AI ...
... integrity, scalability, and reliability enforce responsible AI usage and guardrails. Must-Have Qualifications Solid foundation in enterprise engineering, SDLC, and domain/industry workflows. Demonstrated capability in using copilots and LLM tools for software development tasks. Practical understanding of AI concepts like RAG and ...
... Catalog. This role sits at the intersection of data engineering, model lifecycle management, and AI governance, ensuring that every model — from classical ML to RAG pipelines and autonomous agents — is reproducible, explainable, observable, and production-safe. The incumbent will architect and implement the MLOps and LLMOps ...
... solutions. Manage AI projects with the customer's vision in mind. Automate IT functions and solve specific client problems. Implement LLM & RAG Pipelines Contextualize LLM behavior with client-specific knowledge. Work with customer data science teams. Collaborate with other internal Solutions Architects, Engineering, and Product ...
... required for LLM workloads and use tools like MLflow or TruLens to increase observability and tracking. 3–4 years of hands-on experience as a DevOps / Cloud Engineer with strong focus on Azure services or Snowflake (compute, networking, storage, PaaS). - Solid experience building and maintaining CI/CD pipelines, preferably ...
... scientists, product managers, and engineering teams to operationalize cutting-edge AI/ML innovations. Key Responsibilities Design and deploy GenAI solutions leveraging LLMs (e.g., GPT, LLaMA, Claude, PaLM) for enterprise use cases such as summarization, content generation, semantic search, and conversational AI. Implement RAG pipelines ...
... Hands-on experience with LLMs and Generative AI frameworks- Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworks- Strong understanding of RAG architecture and vector databases (Pinecone, ChromaDB, FAISS, Weaviate, etc.)- Experience with prompt engineering and LLM optimization- Exposure to multi-agent ...
... Hands-on experience with LLMs and Generative AI frameworks- Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworks- Strong understanding of RAG architecture and vector databases (Pinecone, ChromaDB, FAISS, Weaviate, etc.)- Experience with prompt engineering and LLM optimization- Exposure to multi-agent ...
... copilots and LLM tools for rapid coding, debugging, and documentation. Develop front-end and back-end components with seamless integration. Integrate pre-built AI services and APIs into applications implement RAG-based features where relevant. Quality & Speed ~ Combine AI-assisted productivity with engineering best practices ...
... and Agentic AI technologies. Required Technical Skills Strong proficiency in Python Machine Learning fundamentals Natural Language Processing (NLP) Generative AI and Large Language Models (LLMs) Prompt Engineering Retrieval-Augmented Generation (RAG) Embeddings and semantic search Model evaluation and validation techniques