About The Role

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

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-Manager, you will play a pivotal role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Data and Analytics Engineering practice, you will focus on leveraging advanced analytics and statistical techniques to extract insights from large datasets and drive data-driven decision-making. As a Manager, you will motivate, develop, and inspire others to deliver quality, while coaching and leveraging team members' unique strengths to meet client expectations. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way.

In this role at PwC Acceleration Center India, you will take ownership of projects, confirming their successful planning, budgeting, execution, and completion. You will partner with team leadership to validate collective ownership of quality, timelines, and deliverables. Embracing technology and innovation, you will enhance your delivery and encourage others to do the same. Your growing knowledge of business operations will help identify opportunities that contribute to the success of our firm. You will address conflicts or issues, engaging in conversations with clients, team members, and other stakeholders, while upholding professional and technical standards.

Responsibilities

Leading the design and development of advanced data solutions to transform raw data into actionable insights
Guiding teams in leveraging statistical techniques and machine learning algorithms for complex data analysis
Utilizing programming languages such as Python, R, and C++ to enhance data science workflows and predictive modeling
Building and maintaining data pipelines and data lakes to support large-scale data processing and storage
Developing scalable data visualizations to inform strategic decisions and solve business problems
Promoting the use of AI-driven automation and cognitive solutions to optimize data-driven decision making
Mentoring team members to develop skills in data engineering and analytics
Collaborating with stakeholders to address data challenges and drive business growth
Validating data quality and compliance within analytics frameworks
Encouraging innovation and embracing change to enhance delivery and team performance

What You Must Have

At least a Bachelor's degree
At least 4 years of experience
Oral and written proficiency in English required

What Sets You Apart

Over 3 years of 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 risks—prompt injection, jailbreaking, data exfiltration, tool misuse—and 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