Core GenAI/ AI Architects- Senior Manager-Heathcare/Pharma/Lifescience

PwC; Hyderabad, Chennai District, Bengaluru; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

PwC India in Hyderabad seeks a GenAI Architecture lead to translate client objectives into scalable AI solutions, integrating data pipelines, model layers, and digital tooling across complex environments.

You will guide ML, DL, and NLP initiatives, oversee exploratory analysis, statistical modeling, and predictive modeling to inform strategy, coach teams through ambiguity, coordinate multiple workstreams, and communicate tradeoffs to senior stakeholders in clear language.

Qualifications

• GenAI architecture design across client-facing programs.
• Ability to translate business objectives into AI solution designs.
• Experience coaching teams through ambiguity and complex technical decisions.

Responsibilities

• Lead GenAI and AI architecture workstreams for client engagements, translating objectives into practical solution designs.
• Advise stakeholders on AI strategy, use case selection, and delivery approaches across data, analytics, and automation programs.
• Design target-state AI architectures that integrate data pipelines, model layers, and digital tooling across complex environments.
• Guide development of ML, DL, and NLP solutions for business problem solving.
• Oversee exploratory analysis, statistical modeling, and predictive modeling to inform technical direction and investment choices.
• Coordinate technical teams through implementation planning, issue resolution, and delivery across multiple workstreams.
• Apply systems thinking to identify dependencies, data quality gaps, and architecture risks that may affect performance.
• Review AI workflows, model outputs, and data products to validate alignment with client needs.
• Coach team members on AI fluency, analytical thinking, and rapid experimentation methods that support delivery execution.
• Communicate solution tradeoffs, status updates, and recommendations to senior stakeholders in clear language.

Skills

GenAI architecture

AI strategy

Stakeholder communication

Team coaching

Data pipelines

ML/DL/NLP

Delivery planning

Systems thinking

Executive storytelling

Education

Artificial Intelligence and Robotics

Data Processing/Analytics/Science

Computer Science/Engineering

Mathematics/Statistics

Job description

Responsibilities

• Leading GenAI and AI architecture workstreams for client engagements, translating business objectives into practical solution designs
• Advising stakeholders on AI strategy, use case selection, and delivery approaches across data, analytics, and automation programs
• Designing target-state AI architectures that integrate data pipelines, model layers, and digital tooling across complex environments
• Guiding the development of machine learning, deep learning, and natural language processing solutions for business problem solving
• Overseeing exploratory analysis, statistical modeling, and predictive modeling to inform technical direction and investment choices
• Coordinating technical teams through implementation planning, issue resolution, and delivery across multiple workstreams
• Applying systems thinking to identify dependencies, data quality gaps, and architecture risks that may affect solution performance
• Reviewing AI workflows, model outputs, and data products to validate alignment with client needs and delivery objectives
• Coaching team members on AI fluency, analytical thinking, and rapid experimentation methods that support delivery execution
• Communicating solution tradeoffs, status updates, and recommendations to senior stakeholders in clear, concise language

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
• Demonstrating GenAI architecture design across client-facing programs
• Applying systems thinking to uncover root causes and opportunities
• Crafting executive-ready narratives for diverse stakeholder groups
• Coaching teams through ambiguity and complex technical decisions
• Validating AI outcomes and refining solutions from feedback