Senior GenAI / Agentic AI Specialist

As a Senior GenAI / Agentic AI Specialist with 6-8 years of overall experience in AI/ML, including at least 2 years of hands-on expertise in Generative AI and agentic AI systems, your role will involve working with advanced AI models, designing agent workflows, and integrating AI systems into enterprise environments with a focus on scalability, security, and responsible AI practices. Key Responsibilities: - Work with Generative AI technologies including LLMs, diAusion models, and enterprise applications. - Develop and optimize agentic workflows, including multi-agent collaboration and orchestration. - Design and implement Generative AI solutions tailored for enterprise use cases. - Integrate AI agents with APIs, databases, and cloud services. - Apply prompt engineering, context management, and memory handling in agent systems. - Ensure Responsible AI practices are implemented and adhered to. - Deploy AI agents into production environments. - Optimize scalability and performance of AI systems. - Implement robust security practices including IAM, AD, ADLDS, roles, and service accounts. Required Skills & Qualifications: - 6-8 years of overall experience in AI/ML, with at least 2 years in Generative and Agentic AI. - Expertise in generative AI models and prompt engineering techniques. - Proficiency in Python/Java-based AI libraries for developing GenAI applications. - Hands-on experience with agentic AI systems including autonomous agents, multi-step reasoning, and tool orchestration. - Experience with frameworks such as LangGraph, LangChain, AutoGen, CrewAI, and Google ADK. - Practical exposure to MCP server implementation and agent-to-agent communication. - Experience designing and implementing retrieval-augmented generation (RAG) pipelines. - Experience building chatbots for platforms like Microsoft Teams or Slack. - Strong understanding and hands-on experience with vector databases. - Knowledge of context engineering. - Experience with reinforcement learning and fine-tuning LLMs. - Proven experience in building and deploying conversational chat applications. - Proficiency in containerization and orchestration using Kubernetes. - Experience working with SQL and NoSQL databases.,