- Strong hands‑on experience with Python and ML fundamentals
- Proven experience designing Agentic AI systems, including:
- Multi‑agent workflows
- Tool/function calling
- Memory and state management
- Planning and decision loops
- Expertise with LLMs, prompt engineering, and RAG architectures
- Experience with agent frameworks (e.g., LangGraph, CrewAI, AutoGen, similar)
- Familiarity with vector databases, embeddings, and semantic search
- Understanding of AI deployment, monitoring, safety, and evaluation
- Experience working with cloud platforms (Azure / AWS / GCP)
- Strong communication, consulting, and leadership skills
Agentic AI,AI Agents,LLM,RAG,Prompt Engineering,Python,APIs,Vector DB,AWS/Azure/GCP,Docker,CI/CD
- Lead end‑to‑end design and delivery of Agentic AI solutions using LLMs, tools, and orchestration frameworks
- Architect and build multi‑step, goal‑driven AI agents with memory, planning, and tool‑calling capabilities
- Design RAG‑based and tool‑augmented agent workflows for enterprise use cases
- Own model integration, prompt strategies, evaluation, and production readiness
- Act as technical lead for Agentic AI workstreams
- Mentor Data Scientists and AI Engineers on agent design patterns and best practices
- Collaborate with Data Engineering, MLOps, Cloud, and Product teams
- Present technical outcomes, and trade‑offs to client stakeholders
- Contribute to reusable agent frameworks, accelerators, and PoCs
