Senior GenAI
2 days ago
We are seeking experienced Senior GenAI / Agentic AI Specialists 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. This role involves 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.
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