Agentic AI Development: Experience designing and building autonomous AI agents with multi-step reasoning, planning, and task execution.
Python Programming: Solid hands-on development experience in Python.
Large Language Models (LLMs): Practical experience working with LLMs, prompt engineering, and AI-powered applications.
Agent Frameworks & Orchestration: Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
Google Cloud Platform (GCP): Hands-on experience with:
Vertex AI
Cloud Run
GCP Workflows
Other GCP AI/ML services
AI Integration: Experience integrating AI agents with enterprise applications, APIs, databases, and business systems.
Prompt Engineering: Ability to design, optimize, and manage prompts for reliable agent behavior.
AI Memory & Context Management: Experience implementing contextual memory,



retrieval, and conversation management.
AI Evaluation & Monitoring: Ability to measure, monitor, and optimize agent performance, reliability, and cost.
Responsible AI: Understanding of AI governance, model evaluation, safety, bias mitigation, and responsible AI practices.

Nice-to-Have Skills
RAG (Retrieval-Augmented Generation)
Vector Databases (Pinecone, Weaviate, Chroma, Vertex AI Vector Search)
Kubernetes / GKE
MLOps and Model Lifecycle Management
Event-Driven Architectures
Multi-Agent Systems
Enterprise Automation Platforms
CI/CD for AI Applications
Data Engineering on GCP (BigQuery, Dataflow)
GenAI Solution Architecture

📌 Technical Lead Agentic Ai With Gcp Bengaluru (India)
🏢 Capgemini
📍 India