GenAI Architect - Senior Manager

PwC; Hyderabad, Gurugram District, Bengaluru; Hybride; INR 4 200 000 - 6 200 000; Plein temps

Résumé du poste

PwC Hyderabad seeks a senior AI platform engineer to design, deploy, and govern scalable Gen AI and Agentic AI solutions for enterprise clients. You will work across cloud providers, vector databases, and multi-modal AI capabilities to deliver production-grade systems with strong observability.

You will evaluate LLMs and AI governance platforms, selecting cost-effective options while ensuring compliance and performance. Strong collaboration with engineering teams is essential for success.

Qualifications

• Experience designing and deploying enterprise-grade AI platforms.
• Hands-on with agentic AI and workflow orchestration tools.
• Knowledge of vector databases and RAG systems for enterprise knowledge retrieval.

Responsabilités

• Architect and scale Gen AI and Agentic AI solutions for enterprise needs.
• Evaluate LLMs and governance tools to meet cost, latency and compliance goals.
• Collaborate on AI observability, monitoring, and debugging of production systems.
• Promote engineering productivity with AI-powered development tools.

Connaissances

Cloud AI platforms

AI orchestration frameworks

Vector databases

Multi-modal AI

AI governance & observability

LLM selection & cost

AI development tools

Outils

LangGraph

CrewAI

AutoGen

Semantic Kernel

Pinecone

Weaviate

Milvus

Azure AI Search

LangSmith

Arize

GitHub Copilot

Cursor

Windsurf

Description du poste

Role & responsibilities

• Proven experience with enterprise cloud AI platforms like Azure AI Foundry (with Microsoft Fabric and Purview), Amazon Bedrock (with Knowledge Bases and Guardrails), and Google Vertex AI (with BigQuery and Agentspace) for building, governing, and deploying scalable production-grade Gen AI and Agentic AI solutions.
• Hands-on expertise with leading agentic and AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalents for AI workflow automation and orchestration.
• In-depth knowledge of vector databases (Pinecone, Weaviate, Milvus, Azure AI Search) and their application in enterprise Retrieval Augmented Generation (RAG) and knowledge retrieval systems.
• Experience designing and scaling AI solutions that utilize multi-modal capabilities across text, vision, audio, and document understanding to enhance AI functionality.
• Familiarity with AI governance and observability platforms (e.g., LangSmith, Arize) to enable monitoring, tracing, debugging, and compliance of production AI systems, along with expertise in selecting appropriate LLMs (GPT, Claude, Gemini, etc.) based on enterprise cost, latency, and compliance requirements.
• Knowledge of AI-powered development tools (GitHub Copilot, Cursor, Windsurf) to improve engineering productivity and facilitate large-scale AI-driven software development