29 Retrieval-Augmented Generation Jobs - Page 2

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649

Lead AI Engineer About the Role: We are seeking an experienced AI specialist with a strong Computer Science/Engineering background to design, develop, and deploy advanced Generative AI-based solutions. In this role, you will build intelligent AI agents, leverage graph-based RAG techniques, and ensure robust production deployments to solve complex challenges in the Architecture, Engineering, and Construction (AEC) domain. Key Responsibilities Collaborate with stakeholders to align AI initiatives with business goals. Lead and mentor a team of ML engineers and data scientists. Design, develop, and deploy enterprise-grade RAG systems that deliver accurate, context-aware responses in production environments. Incorporate AI agents and graph-based techniques (e.g., GraphRAG) to enable enhanced contextual data retrieval and support complex query relationships. Implement robust evaluation frameworks to measure and enhance RAG system effectiveness. Create scalable pipelines for document processing, embedding generation, and knowledge base management. Build monitoring systems to track performance, detect issues, and ensure RAG system reliability. Architect cloud-native solutions that can scale to handle enterprise document volumes and query loads. Explore and integrate cutting-edge techniques in Generative AI, including but not limited to model fine-tuning. Qualifications & Skills A strong foundation in Computer Science or Engineering with 5-10 years' experience in NLP, Computer Vision, Deep Learning, Machine Learning, or related field. Extensive experience with LLMs and related technologies (e.g., embedding models, vector databases, etc.). Proven expertise in developing production-grade RAG systems. Knowledge of graph-based RAG techniques (e.g., Graph RAG or alternatives). Proficiency in Python and familiarity with Generative AI frameworks such as Hugging Face, Lang Chain, Llama Index, Prompt flow, Auto Gen, etc. Hands-on experience with cloud-based AI deployments (Azure preferred). Experience in LLM fine-tuning and optimization (e.g., LoRA) is a plus. Exposure to multi-modal RAG systems and LLMOps frameworks. Familiarity with deep learning architectures (e.g., Transformers, CNNs, GANs) and modern ML frameworks (e.g., PyTorch, Tensorflow, etc.).

Greetings from idexcel technologies: Role & responsibilities We are seeking a Data Scientist with a strong background in Machine Learning, Natural Language Processing (NLP), Generative AI, and Retrieval-Augmented Generation (RAG). The ideal candidate will possess 1+ years of hands-on experience in developing and deploying advanced data-driven solutions. You will play a key role in our AI-CoE team, contributing to cutting-edge projects that drive innovation and business value. A special focus area for this role would be to build AI enabled products that would result in the creation of monetizable product differentiators for Tata Communications products and services. Detailed job description & Key Responsibilities: Develop, Test, and Deploy machine learning models for various business and Telco use cases. Perform data preprocessing, feature engineering and ML/DL model evaluation. Optimize and fine-tune models for performance and scalability. Good understanding of NLP concepts and projects involving entity recognition, text classification, and language modelling like GPT/Llama/Claude/Grok Build and refine RAG models to improve information retrieval and answer generation systems. Integrate RAG methods into existing applications to enhance data accessibility and user experience. Work closely with cross-functional teams including software engineers, product managers, and domain experts. Communicate technical concepts to non-technical stakeholders effectively. Document processes, methodologies, and model development for internal and external stakeholders. Skills: Strong knowledge of probability and statistics. Working knowledge of machine learning and deep learning skills. Strong knowledge of programming knowledge Python, SQL and commonly used frameworks & tools – PyTorch, Sci-kit, NumPy, Gen AI tools like Lang chain/llama Index Working knowledge of MLOPs principles and implementing projects with Big Data in batch and streaming mode. Excellent problem-solving skills and a proactive attitude. Strong communication and teamwork abilities. Ability to manage multiple projects and meet deadlines

ZENSAR - OPPORTUNITY FOR Gen AI with Python Engineer” Apply Here: - https://forms.office.com/r/nVP0Mg5eeE Dear Aspirant, Greetings from Zensar!! We are thrilled to offer you an excellent opportunity to join our team as a Gen AI with Python Engineer professional . Experience Required: 6 - 9 Years Location: Pune, Bangalore, Chennai, Hyderabad (Hybrid) LLM Applications & Agentic Frameworks Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP. Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks. Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports. Rapidly explore and showcase the art of the possible through functional, demonstrable POCs Advanced AI Experimentation Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use. Create and leverage synthetic datasets to simulate edge cases and scale training. Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability) Evaluate emerging agent communication standards — A2A (Agent-to-Agent) and MCP (Model Context Protocol) Business Alignment & Cross-Team Collaboration Translate ambiguous requirements into structured, AI-enabled solutions. Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders Good-To-Have Microsoft Copilot Studio DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Qualifications 6–9 years of experience in software development or AI/ML engineering At least 3 years working with LLMs, GenAI applications, or agentic frameworks. Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration Proven track record of developing functional AI prototypes beyond notebooks. Strong presentation and storytelling skills to clearly convey GenAI concepts and value. Ability to independently drive AI experiments from ideation to working demo. Role & responsibilities Preferred candidate profile