Generative AI 2-7 yrs

Job Summary

We are seeking a highly motivated Generative AI Engineer with hands-on experience in Generative AI, Agentic AI, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), and AI Agent Frameworks. The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade AI applications powered by Large Language Models (LLMs), autonomous agents, and advanced retrieval systems.

Key Responsibilities

• Design and develop AI-powered applications using Generative AI and Large Language Models (LLMs).
• Build and deploy Agentic AI solutions capable of autonomous reasoning and task execution.
• Implement RAG architectures using vector databases and enterprise knowledge sources.
• Develop integrations using Model Context Protocol (MCP) for AI tool and data connectivity.
• Build multi-agent systems using modern Agent Frameworks.
• Fine-tune prompts and optimize LLM performance for business use cases.
• Develop AI workflows for document processing, knowledge management, and conversational AI.
• Integrate AI services with enterprise applications using APIs and microservices.
• Collaborate with data scientists, product teams, and software engineers to deliver AI solutions.
• Evaluate emerging AI technologies and recommend best practices.

Required Skills

• 2-6 years of software development experience.
• Strong proficiency in Python.
• Hands-on experience with Generative AI and Large Language Models.
• Experience building RAG (Retrieval-Augmented Generation) pipelines.
• Knowledge of Agentic AI architectures and autonomous AI agents.
• Experience with MCP (Model Context Protocol) integration and AI tooling.
• Hands-on experience with AI Agent Frameworks such as:
• LangGraph
• LangChain
• CrewAI
• AutoGen
• Semantic Kernel
• LlamaIndex
• Experience with Vector Databases:
• Pinecone
• ChromaDB
• Weaviate
• Milvus
• FAISS
• Experience with OpenAI, Azure OpenAI, Claude, Gemini, or Open Source LLMs.
• Strong understanding of Prompt Engineering and AI application development.
• Experience with REST APIs and Microservices.
• Familiarity with Git, Docker, and Kubernetes.

Preferred Skills

• Experience with AI Observability and Evaluation Tools.
• Knowledge of Fine-Tuning and Model Optimization.
• Experience with Cloud Platforms (Azure, AWS, GCP).
• Exposure to NLP, Machine Learning, and Deep Learning concepts.
• Knowledge of CI/CD for AI deployments (LLMOps).
• Experience building AI Chatbots, AI Assistants, and Enterprise Search solutions.

Educational Qualification

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or related field.