- 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)
🏢 Capgemini
📍 Bengaluru