About this Generative AI Architect- Manager role at PwC
Industry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
ManagerJob 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 leverage advanced technologies and techniques to design and develop robust data solutions for clients. As a Manager, you will enhance your leadership style by motivating, developing, and inspiring others to deliver quality. You will be responsible for coaching, leveraging team members' unique strengths, and managing performance 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 embrace technology and innovation to enhance your delivery and encourage others to do the same. You will take ownership of projects, validating their successful planning, budgeting, execution, and completion. You will also address conflicts or issues, engaging in difficult conversations with clients, team members, and other stakeholders, escalating where appropriate. This position offers the opportunity to develop skills outside your comfort zone and encourage others to do the same, all while upholding and reinforcing 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 advanced analytics and statistical techniques for data-driven decision making
- Utilizing machine learning and artificial intelligence to enhance data science workflows and predictive modeling
- Overseeing the creation and deployment of data visualizations to solve complex business problems
- Managing data engineering processes, including data pipeline, data lake, and data quality initiatives
- Collaborating with stakeholders to identify opportunities for optimizing data utilization and improving business performance
- Mentoring team members to develop skills in data science algorithms and complex data analysis
- Promoting the adoption of innovative technologies and leading practices in data and analytics engineering
- Confirming data integrity and compliance within analytics frameworks
- Encouraging a culture of intellectual curiosity and continuous learning within the team
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
Travel Requirements
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