Agentic AI Lead/ Architect (Python)

Key Responsibilities:

• Design and architect Agentic AI and multi-agent systems using Python and modern LLM technologies.
• Lead development of autonomous AI agents capable of planning, reasoning, tool usage, and task execution.
• Design solutions using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies.
• Integrate LLMs, RAG pipelines, vector databases, APIs, and enterprise data sources.
• Develop reusable AI-agent architectures, orchestration patterns, and tool-calling frameworks.
• Define AI architecture, technical standards, security, governance, and best practices.
• Build scalable AI services and APIs using Python, FastAPI, and cloud-native technologies.
• Implement prompt engineering, context management, memory, evaluation, and guardrails.
• Collaborate with product, data, engineering, and business teams to identify and deliver AI use cases.
• Lead technical design reviews and mentor AI/ML engineers.
• Monitor AI applications for performance, accuracy, reliability, cost, and latency.
• Support deployment using AWS, Azure, or Google Cloud Platform, along with CI/CD and MLOps practices.

Required Skills:

• Strong hands-on experience with Python.
• Deep understanding of Generative AI, LLMs, NLP, and Agentic AI.
• Experience with LangChain/LangGraph, AutoGen, CrewAI, or comparable agent frameworks.
• Strong knowledge of RAG, embeddings, vector databases, and semantic search.
• Experience with LLM APIs such as OpenAI, Azure OpenAI, Anthropic, or Google Gemini.
• Experience developing REST APIs using FastAPI or Flask.
• Knowledge of cloud platforms and AI/ML services.
• Strong understanding of AI security, responsible AI, observability, and governance.
• Excellent architecture, leadership, communication, and problem-solving skills.