Generative AI Architect - Manager

Pricewater House Coopers Service Delivery Center Bangalore; Gurugram District, Bengaluru, Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

PricewaterhouseCoopers Service Delivery Center Bangalore is seeking a seasoned AI Architect to lead the development and scaling of enterprise Generative AI initiatives. You will drive multi-region deployments, optimize throughput and cost, and ensure robust AI interoperability across systems.

The ideal candidate brings hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, and strong Python skills, plus proficiency in MCP/A2A protocols and modern RAG architectures to deliver

Qualifications

• Experience in developing and scaling Generative AI projects from prototypes to enterprise production.
• Proven expertise implementing AI interoperability protocols at scale for seamless system integration.
• Strong cloud AI platform experience for building production-grade agentic AI solutions.

Responsibilities

• Experience in developing and scaling Generative AI projects from prototypes to enterprise production, managing throughput, latency, cost, and multi-region deployments.
• Proven expertise implementing AI interoperability protocols like MCP and A2A at scale for seamless system integration.
• Skilled in using enterprise cloud AI platforms such as Azure AI Foundry, Amazon Bedrock, and Google Vertex AI to build and deploy production-grade agentic AI solutions.
• Advanced Python programming skills and hands-on experience with agentic AI frameworks including LangChain, LangGraph, CrewAI, and AutoGen for building robust generative AI applications.
• Deep understanding of advanced Retrieval Augmented Generation (RAG) architectures and traditional AI/ML fundamentals.

Skills

Generative AI

Python programming

LLM security

AI risk management

Distributed systems

Tools

Kubernetes

Docker

Serverless

LangChain

LangGraph

CrewAI

AutoGen

Azure AI Foundry

Amazon Bedrock

Google Vertex AI

Job description

Role & responsibilities

• Experience in developing and scaling Generative AI projects from prototypes to enterprise production, managing throughput, latency, cost, and multi-region deployments.
• Proven expertise implementing AI interoperability protocols like MCP (Model Context Protocol) and A2A (Agent-to Agent) at scale for seamless system integration.
• Skilled in using enterprise cloud AI platforms such as Azure AI Foundry, Amazon Bedrock, and Google Vertex AI to build and deploy production-grade agentic AI solutions.
• Advanced Python programming skills and hands-on experience with agentic AI frameworks including LangChain, LangGraph, CrewAI, and AutoGen for building robust generative AI applications.
• Deep understanding of advanced Retrieval Augmented Generation (RAG) architectures (Graph RAG, Vectorless RAG, Hybrid RAG) and traditional AI/ML fundamentals like model building, fine-tuning, and evaluation.
• Strong knowledge of LLM security risksprompt injection, jailbreaking, data exfiltration, tool misuseand experience designing defense-in-depth safeguards within agentic system architectures.
• Expertise in containerization and cloud-native orchestration (Kubernetes, Docker, serverless) and event-driven architectures for scalable deployment of agentic AI workloads; holds relevant AI or solution architecture certifications.