Gen AI

Job description

**Job Title: GenAI Engineer (511 Years) – Immediate Joiners Preferred** **Experience:** 5 – 11 Years **Employment Type:** Full-Time **Job Summary** We are seeking an experienced **GenAI Engineer** with strong expertise in **Generative AI, Agent Frameworks, Agentic AI, RAG (Retrieval-Augmented Generation), and MCP (Model Context Protocol)**. The ideal candidate will design and implement intelligent, scalable AI systems leveraging LLMs, multi-agent workflows, and contextual reasoning. Candidates who can **join immediately or within short notice periods** are highly preferred. **Key Responsibilities** - Design and develop **GenAI-powered applications** using modern LLM ecosystems - Build and optimize **RAG pipelines** for context-aware AI solutions - Develop **Agentic AI systems** using frameworks like LangChain, AutoGen, CrewAI, or similar - Implement and manage **multi-agent orchestration and workflows** - Utilize **Model Context Protocol (MCP)** for advanced prompt and context management - Integrate LLMs with enterprise systems, APIs, and databases - Fine-tune prompts and evaluate model performance (accuracy, latency, cost) - Ensure security, scalability, and reliability of AI solutions - Collaborate with cross-functional teams including data engineering, product, and DevOps - Stay updated on emerging GenAI tools, frameworks, and best practices **Required Skills & Qualifications** - Strong experience in **Generative AI / LLM-based application development** - Hands-on experience with **RAG architectures** (vector DBs like FAISS, Pinecone, Weaviate, etc.) - Expertise in **Agent Frameworks** (LangChain, AutoGen, CrewAI, etc.) - Experience building **Agentic AI systems / multi-agent orchestration** - Knowledge of **MCP (Model Context Protocol)** or equivalent context-management approaches - Strong programming skills in **Python** - Experience working with **OpenAI, Azure OpenAI, or similar LLM APIs** - Familiarity with **prompt engineering and evaluation techniques** - Experience with **REST APIs, microservices architecture** **Preferred Qualifications** - Experience with **fine-tuning / embedding models** - Familiarity with **vector databases and semantic search** - Exposure to **cloud platforms (AWS / Azure / GCP)** - Knowledge of **ML Ops / LLM Ops tools** - Experience with **streaming pipelines and real-time AI systems** - Understanding of **data privacy and AI governance**