IN_ Director _Agentic + GenAI__Data & Analytics_ Advisory_ Mumbai
Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
DirectorJob Description & Summary
At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
Responsibilities:
Strategic Leadership
Define and execute the long-term roadmap for Agentic AI and GenAI initiatives.
Identify and prioritize opportunities where autonomous agents and generative AI can drive business value.
Collaborate with executive leadership to align AI strategy with overall business goals.
Must have Technology & Research Oversight
Lead architecture and hands-on development of intelligent agent frameworks (e.g., goal-driven, tool-using agents).
Oversee the application of LLMs, multimodal models, and fine-tuning strategies for domain-specific use cases.
Evaluate and integrate emerging GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.).
• Advanced proficiency in Python.
• Extensive experience with LLM frameworks (Hugging Face, Transformers, LangChain) and prompt engineering techniques.
Must have:
• Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation
• Expertise in feature engineering, embedding optimization, and dimensionality reduction
• Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing
• Experience with RAG systems, vector databases, semantic search implementation and Knowledge graph.
• Proficiency in LLM optimization techniques including quantization and knowledge distillation
• Understanding of MLOps practices for model deployment and monitoring
Team Management & Collaboration
Build, mentor, and scale a world-class team of AI researchers, ML engineers, and product managers.
Foster a strong interdisciplinary culture of innovation and experimentation.
Collaborate cross-functionally with data engineering, product, legal, and design teams.
Operational Excellence
Oversee data pipelines, model training, inference infrastructure, and model governance.
Establish benchmarks and evaluation protocols for agent behavior, safety, and performance.
Ensure ethical and responsible AI development practices are followed.
Good to have Domain/functional knowledge
Experience in financial services domain will be a plus.
Experience in solving use cases in Asset management, Wealth management or investment banking using AI/ML.
Mandatory skill sets:
GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.).
Preferred skill sets:
Lang Experience in industries such as finance, consulting
Track record of publishing or contributing to open-source AI frameworks.
Understanding of regulatory, ethical, and societal implications of autonomous AI system
Years of experience required:
14-17
Education qualification:
B.Tech / M.Tech / MBA / MCA
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Engineering, Master of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Agilent Technologies GeneSpring GXOptional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Coaching and Feedback, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling {+ 50 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
June 26, 2026AI Engineering pay context
Based on 640 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $201K/year, with most offers between $162K and $246K (10th–90th percentile: $131K–$285K).
See the full AI Engineering salary breakdown →