Senior GenAI Engineer

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI applications.
• Build and optimize LLM-powered applications using GPT, Claude, Gemini, Llama, and other open-source models.
• Develop advanced RAG pipelines using LangChain, LlamaIndex, and vector databases.
• Implement multi-agent AI systems using LangGraph, CrewAI, and AutoGen.
• Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions.
• Integrate LLMs with enterprise applications using REST APIs, FastAPI, and microservices.
• Implement prompt engineering, fine-tuning, embeddings, and semantic search techniques.
• Design and deploy scalable AI solutions on AWS, Azure, or Google Cloud.
• Build CI/CD pipelines and implement LLMOps/MLOps best practices.
• Optimize LLM performance, latency, token consumption, and operational costs.
• Implement AI security, governance, guardrails, and responsible AI practices.
• Collaborate with architects, data scientists, product managers, and business stakeholders.

We are seeking a highly experienced Senior Generative AI Engineer with 10+ years of overall IT experience and strong hands-on expertise in developing, deploying, and scaling enterprise-grade Generative AI and Agentic AI solutions.

The ideal candidate should have extensive experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, AI agents, cloud platforms, and MLOps., * 10+ years of overall IT/software engineering experience.

• 3+ years of hands-on AI/ML or Generative AI experience, including production GenAI implementations.
• Strong Python development experience.
• Proven experience building production-ready LLM and RAG applications.
• Hands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, or AutoGen.
• Experience integrating vector databases and enterprise data sources.
• Strong understanding of cloud-native architecture and microservices.
• Experience deploying AI applications using Docker and Kubernetes.
• Knowledge of LLM evaluation, observability, security, and performance optimization.
• Excellent communication, problem-solving, and technical leadership skills., * Experience designing enterprise-scale Agentic AI solutions.
• Knowledge of Model Context Protocol (MCP).
• Experience with multimodal AI (text, image, audio, and video).
• Experience implementing AI governance and responsible AI frameworks.
• Knowledge of advanced RAG architectures, GraphRAG, and knowledge graphs.
• Experience with distributed systems and high-performance AI infrastructure.