Technical Lead Agentic Ai With Gcp Capgemini Pune Bengaluru Delhi Ncr

Vibehackers; Pune District, Bengaluru; Hybrid; INR 2,500,000 - 5,000,000; Full time

Job summary

Vibehackers in India seeks a Technical Lead for Agentic AI with Google Cloud Platform expertise. You will design, build, and deploy autonomous AI agents using LangChain/AutoGen, integrating them with enterprise systems and ensuring robust performance.

The role emphasizes multi-step reasoning, orchestration, and responsible AI practices, with hands-on Python development and collaboration across teams to deliver production-grade AI solutions on GCP.

Qualifications

• Strong Python development experience for production AI systems.
• Hands-on experience with LLMs, prompt engineering, and AI-powered applications.
• Experience designing and building autonomous/multi-step agent systems and orchestration.
• Familiarity with Google Cloud Platform components (Vertex AI, Cloud Run, Dataflow).

Responsibilities

• Design and build autonomous AI agents with multi-step reasoning, planning, and task execution.
• Implement and maintain agent orchestration and frameworks (e.g., LangChain, LangGraph, AutoGen, Semantic Kernel).
• Develop production-grade code in Python for AI applications and integrations.
• Integrate AI agents with enterprise applications, APIs, databases, and business systems.
• Implement contextual memory, retrieval, and conversation management for agents.
• Measure, monitor, and optimize agent performance, reliability, and cost.
• Apply responsible AI practices: governance, safety, bias mitigation, and model evaluation.
• Lead technical decisions, provide architecture guidance, and collaborate with cross-functional teams.

Skills

Python Programming

Agent Design

LLMs & Prompt Engineering

GCP & Vertex AI

System Architecture

Team Leadership

Tools

LangChain

AutoGen

LangGraph

Semantic Kernel

GCP

Vertex AI

Kubernetes

Job description

Technical Lead Agentic Ai With Gcp Capgemini Pune Bengaluru Delhi Ncr

Directly focused on agentic/vibe-style coding: building LLM-driven autonomous agents using LangChain/AutoGen and GCP tooling.

About the Role

Technical Lead responsible for designing, building, and deploying agentic AI systems that perform multi-step reasoning and task execution, primarily on Google Cloud Platform. Lead hands-on development in Python, work with LLMs and agent frameworks (e.g., LangChain, AutoGen), and integrate AI agents with enterprise systems while ensuring performance, monitoring, and responsible AI practices.

Job Description

Role

Lead the design and development of agentic AI solutions that perform multi-step reasoning, planning, and autonomous task execution. Own architecture, integration, and operationalization of AI agents on Google Cloud Platform.

Key Responsibilities

• Design and build autonomous AI agents with multi-step reasoning, planning, and task execution.
• Implement and maintain agent orchestration and frameworks (e.g., LangChain, LangGraph, AutoGen, Semantic Kernel).
• Develop production-grade code in Python for AI applications and integrations.
• Integrate AI agents with enterprise applications, APIs, databases, and business systems.
• Implement contextual memory, retrieval, and conversation management for agents.
• Measure, monitor, and optimize agent performance, reliability, and cost.
• Apply responsible AI practices: governance, safety, bias mitigation, and model evaluation.
• Lead technical decisions, provide architecture guidance, and collaborate with cross-functional teams.

Requirements

• Strong hands-on development experience in Python.
• Practical experience with large language models (LLMs), prompt engineering, and AI-powered applications.
• Experience designing and building autonomous/multi-step agent systems and orchestration.
• Hands-on experience with Google Cloud Platform components, including Vertex AI, Cloud Run, and GCP Workflows.
• Experience integrating AI solutions with enterprise systems, APIs, and databases.
• Skills in prompt engineering, AI memory/context management, and agent evaluation/monitoring.
• Understanding of Responsible AI principles and practices.

Nice-to-have

• Retrieval-Augmented Generation (RAG) experience.
• Experience with vector databases: Pinecone, Weaviate, Chroma, Vertex AI Vector Search.
• Kubernetes / GKE and MLOps/model lifecycle management experience.
• Familiarity with event-driven architectures, multi-agent systems, enterprise automation platforms, CI/CD for AI, and GCP data services (BigQuery, Dataflow).
• Experience in GenAI solution architecture.

Python LangChain LangGraph CrewAI AutoGen Semantic Kernel Google Cloud Platform (GCP) Vertex AI Vertex AI Vector Search Cloud Run GCP Workflows Pinecone Weaviate Chroma Kubernetes GKE BigQuery Dataflow

Skills

System Architecture Team Leadership Python Programming Prompt Engineering Agent Design AI Integration Context & Memory Management Model Evaluation & Monitoring Responsible AI MLOps Event-Driven Architecture Enterprise Automation CI/CD