Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

& Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis.

You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life.

Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.

At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations.

&

Summary: We are hiring an AI Transformation Leader to drive AI-led business transformation across enterprise functions. Own the full transformation arc from workflow assessment and stakeholder alignment to solution shaping, pilot rollout, adoption, and value realization. Evaluate AI architectures, guide platform choices, challenge solution designs, and work closely with engineering, architecture, data, and enterprise systems teams. Combine business transformation leadership, enterprise stakeholder management,



AI/GenAI solution understanding, process redesign, adoption capability, and strong enterprise technology fluency.

Responsibilities: Assess current-state business processes and identify high-value AI transformation opportunities. Lead end-to-end transformation from discovery, prioritization, redesign, pilot, rollout, and adoption. Partner with business leaders, IT, analytics, and architecture teams to shape scalable AI initiatives.

Translate business problems into transformation roadmaps, use cases, and measurable outcomes. Drive workshops, stakeholder alignment, and business case development. Guide AI solution decisions in line with approved enterprise platforms, data architecture, security, and governance.

Prevent shadow AI and fragmented tooling by channeling initiatives through enterprise standards. Support pilot execution and ensure sustainable business adoption and value realization. Influence future-state workflows, operating models, governance, and human-in-the-loop controls.

Mandatory skill sets: 12+ years in business transformation, digital transformation, enterprise transformation, or AI-led transformation. Strong understanding of business domains such as Finance and Sales. Proven experience owning transformation programs end-to-end, beyond technical component delivery. Solid stakeholder management with business, IT, architecture, operations, and leadership teams.

Experience in process discovery, workflow redesign, operating model change, and adoption. Ability to identify AI opportunities and convert them into business-aligned execution roadmaps.

Experience in large enterprise environments with governance, InfoSec, and architecture constraints. Strong understanding of AI/ML and GenAI use cases, LLM-powered solutions, enterprise copilots, conversational AI, and intelligent assistants. Good understanding of RAG architectures, vector embeddings, prompt engineering, context engineering, agentic workflows, multi-agent systems, and human-in-the-loop AI design.

Familiarity with LangChain,



LangGraph, MCP / agent-to-agent orchestration concepts, scalable AI service design, microservices, API-based integration, cloud-native architecture, and production-grade AI solution approaches. Exposure to Azure / AWS Cloud, vector databases, Salesforce, Oracle EBS or similar ERP platforms, Snowflake, REST APIs, MCP, integration architecture, and enterprise data flows. Understanding of responsible AI, enterprise governance, data security and compliance, CI/CD, production deployment, monitoring, and support expectations for enterprise AI products.

Preferred skill sets: Consulting or enterprise transformation leadership background.

Experience in Finance, Sales, Marketing, Customer Success, RevOps, or Enterprise Operations. Prior exposure to AI transformation programs in business functions, not just standalone AI product builds. Ability to bridge business strategy with technical solutioning. Strong competencies in AI strategy, prospect identification, process redesign, technology evaluation, change management, adoption, governance, risk awareness, executive communication, and cross-functional leadership.

Years of experience required: 12+ years Education qualification: BE, B.Tech, ME, M.Tech, MBA, MCA or equivalent qualification preferred Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Bachelor of Engineering, Bachelor of Technology, MBA (Master of Business Administration)

Degrees/Field of Study preferred

Certifications (if blank, certifications not specified)

Required Skills

Artificial Intelligence (AI)

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

August 10, 2026

📌 IN_Senior Associate – AI Transformation – Data and Analytics – Advisory – Bangalore (Bengaluru)
🏢 PwC
📍 Bengaluru