IN_Senior Manager_AI/ML_GCC_Advisory_Pune

Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Senior Manager
Job Description & 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. "
Job Description & Summary:
We are seeking to recruit an SM/ Director with AI proficiency who can help build practice and drive sales in the GCC segment.
Responsibilities:
AI & Analytics Transformation Leadership (40%)
Lead large, complex, multi-workstream AI and data transformation programmes for marquee clients — enterprise data modernisation, GenAI/Agentic AI deployment, MLOps industrialisation, and analytics operating-model redesign
Act as the senior technical authority: review solution architectures, model design choices, evaluation frameworks, and Responsible AI controls — not just delegate them
Drive AI adoption and change management: use-case portfolio definition, value cases, AI Centre of Excellence stand-up, and workforce enablement
Establish measurable outcomes — cycle-time reduction, cost-to-serve, decision quality, and ROI — and hold delivery accountable to them
Business Development & Sales (30%)
Own an annual sales/origination target; build and convert a qualified pipeline across new GCC accounts
Lead pursuits end-to-end: qualification, win strategy, solutioning, commercials, orals, and negotiation
Build CXO-level relationships (CDO, CIO, CTO, CAIO, Head of Digital) and grow accounts from project to programme to platform
Practice & Capability Building (20%)
Build reusable IP, accelerators, and industry AI solutions; contribute to PwC's GenAI/Agentic AI asset library
Scale the team: hiring, capability roadmaps, technical mentoring, and career sponsorship for Managers and Senior Managers
Champion Responsible AI — governance, model risk, bias/fairness testing, explainability, and alignment to the EU AI Act, India's DPDP Act, and RBI/SEBI/IRDAI expectations
Thought Leadership & Market Presence (10%)
Author points of view, whitepapers and industry reports; represent PwC at NASSCOM, industry forums, and client roundtables
Shape the market narrative on enterprise AI in India
Mandatory skill sets:
Technology Consulting Experience
Minimum 7+ years in a client-facing technology/management consulting role, owning delivery and commercial outcomes. Must have operated in a billable, engagement-led model.
Hands-on AI Leader
Demonstrable hands-on depth — has personally built, deployed and scaled ML/GenAI solutions (not purely advisory/PMO). Must be able to whiteboard a RAG architecture, critique an evaluation framework, and debate model trade-offs credibly. Must have led at least 2–3 enterprise AI transformations from strategy through production..
Firm Pedigree
Current or recent experience at a Big 4 (Deloitte, EY, KPMG), Accenture Technology, CG or a Tier-1 GCC/Global tech consulting arm at Senior Manager / Associate Director / Director level.
Sales Background
Proven origination track record — must be able to evidence personally sold/influenced revenue (indicatively ₹10–20 Cr+ cumulative or a consistent annual target). Comfortable owning a number.
Technical Depth Expected
Must have working, current fluency in:
GenAI & Agentic AI — LLM selection & fine-tuning, RAG architectures, agent orchestration (LangChain/LangGraph, Semantic Kernel, AutoGen), prompt & context engineering, evaluation/guardrails
Classical ML & Data Science — supervised/unsupervised learning, forecasting, NLP, computer vision, causal inference, optimisation
Modern Data Stack — Databricks, Snowflake, Azure Fabric/Synapse, AWS (SageMaker/Bedrock), GCP (Vertex AI), dbt, Kafka, lakehouse & data mesh architectures
MLOps/LLMOps — CI/CD for models, feature stores, monitoring, drift detection, model registries, cost & latency optimisation
Governance — data governance, master data, Responsible AI frameworks, model risk management
Behavioral & Leadership Competencies
Executive presence — credible and persuasive with boards and CXOs; able to translate technical complexity into business language
Commercial instinct — spots and shapes opportunity in every client conversation
Player-coach — willing to go deep into a problem, and equally capable of scaling through others
Resilience & ambiguity tolerance — thrives in undefined, fast-moving transformation contexts
Ethical rigour — uncompromising on quality, independence and Responsible AI
Preferred skill sets:
Sector depth in BFSI, Consumer/Retail, Pharma/Life Sciences, or Manufacturing
Experience serving Global Capability Centres (GCCs) in India
Cloud/platform certifications — Azure AI Engineer, AWS ML Specialty, Databricks Data Engineer/ML Professional, GCP Professional ML Engineer
Published research, patents, or open-source contributions in AI/ML
Experience with AI-enabled managed services or outcome-based commercial models
Years of experience required:
10–15 years total post-qualification experience, with a clear trajectory to Director.
Education qualification:
B.E./B.Tech from IIT / NIT / BITS / Tier-1 engineering institute, and/or MBA from IIM / ISB / XLRI / FMS / MDI / top global school. Advanced degree (M.S./Ph.D.) in CS, Statistics, Data Science or Applied Mathematics is a strong plus.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Business Administration, Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills
Data Engineering
Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, AI Fluency, AI-Human Collaboration, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Data Architecture, 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

Work arrangement
No