Generative AI Architect- Senior Manager

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Manager

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a Generative AI Architect- Senior Manager you will lead the design of AI-enabled solutions that turn business challenges into practical data and analytics engineering outcomes, within our Data and Analytics Engineering practice. As a Senior Manager you will use strategic judgment, influence, and coaching skills to guide multi-disciplinary teams through complex delivery, shape client conversations at a senior level, and move ideas from concept to execution while maintaining operational excellence.

In this role at PwC, you will focus on generative AI architecture, solution design, and delivery support across data science and AI initiatives, drawing on advanced technologies, statistical methods, and storytelling to translate data into decisions. You will also contribute to team development, mentor others through ambiguity, and validate that technical direction aligns with client priorities and the broader business context.

Responsibilities

- Lead evaluation, benchmarking, and implementation of scalable, secure, and compliant Agentic AI frameworks aligned with enterprise business use cases and organizational strategies.

- Drive technical standardization and maturity in Generative and Agentic AI development by creating reusable orchestration blueprints, prompt engineering guides, best practices, and integration patterns to ensure consistent delivery in complex programs.

- Define scalable multi-agent system design patterns including tool usage, memory management, task routing, agent communication, human-in-the-loop processes, and orchestration frameworks.

- Establish evaluation frameworks to assess Agentic AI solution performance, focusing on reasoning, tool reliability, task completion, hallucination mitigation, and autonomous decision quality for production readiness and continuous improvement.

- Design enterprise Retrieval

- Augmented Generation (RAG) architectures optimizing retrieval processes, embeddings, chunking, and reranking aligned with business goals and data governance, while mentoring AI engineering teams and collaborating with stakeholders to translate objectives into AI roadmaps.

- Manage client engagements including discovery, demos, proposal development, and delivery planning, leveraging strong DevOps, LLMOps, containerization, and CI/CD pipeline expertise to ensure successful, trusted partnerships and stay updated on Agentic AI and Generative AI advancements

What You Must Have

- At least a Bachelor's & Master's Degree

- 12+ years of experience in technical/technology roles

- Oral and written proficiency in English required

What Sets You Apart

- 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.

Travel Requirements

Not Specified

Job Posting End Date