IN_Manager_AI/ML Engineer_GCC_Advisory_Hyderabad

PwC; Hyderabad; On-site; INR 2,500,000 - 3,600,000; Full time

Job summary

PwC is seeking a Manager within Data, Analytics & AI to lead the development of ML/AI pipelines and production deployments. You will design RAG systems, agentic AI solutions, and scalable LLM architectures, while mentoring team members and driving data-driven decision making across stakeholders.

With 7–12 years of experience, you will collaborate in Agile teams to deliver high-impact analytics solutions, stay current with AI/GenAI trends, and contribute to enterprise data platform initiatives in

Qualifications

• Experience of 7–12 years in data, analytics, or AI leadership roles.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (60% above).
• Degrees/Field of Study: Bachelor of Technology or Bachelor of Engineering.

Responsibilities

• Build end-to-end ML/AI pipelines (data → model → deployment → monitoring).
• Develop and deploy ML, Deep Learning, NLP, and GenAI models in production.
• Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering.
• Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, memory.
• Build and optimise time series forecasting models (demand forecasting, inventory planning).
• Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance.
• Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams.

Skills

Analytical thinking

Data-driven insights

AI fluency

Communication

Coaching and feedback

Dashboard creation

Problem solving

Education

Bachelor's or Master's in CS/Engineering

Tools

Snowflake

Alteryx

Job description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job 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.

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

Responsibilities

• Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
• Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
• Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
• Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
• Build and optimise time series forecasting models (demand forecasting, inventory planning)
• Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
• Optimize models for performance, cost, and latency
• Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
• Design scalable LLM inference architectures for efficient deployment
• Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
• Debug, optimise, and enhance ML models for quality and performance improvements
• Mentor team members and present technical findings to diverse audiences
• Stay current with AI/GenAI trends and evaluate emerging tools and frameworks

Mandatory skill sets

• Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
• Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
• Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
• Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
• Build and optimise time series forecasting models (demand forecasting, inventory planning)
• Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
• Optimize models for performance, cost, and latency
• Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
• Design scalable LLM inference architectures for efficient deployment
• Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
• Debug, optimise, and enhance ML models for quality and performance improvements
• Mentor team members and present technical findings to diverse audiences
• Stay current with AI/GenAI trends and evaluate emerging tools and frameworks

Preferred skill sets

• Build end-to-end ML/AI pipelines (data → model → deployment → monitoring)
• Develop and deploy ML, Deep Learning, NLP, and GenAI models in production
• Design and implement RAG systems — retrieval, chunking, embeddings, vector search, and prompt engineering
• Build Agentic AI solutions — autonomous agents, multi-agent workflows, tool-calling, planning, and memory
• Build and optimise time series forecasting models (demand forecasting, inventory planning)
• Implement MLOps pipelines — CI/CD, model monitoring, drift detection, governance
• Optimize models for performance, cost, and latency
• Integrate AI systems with enterprise APIs, data platforms, and customer-facing applications
• Design scalable LLM inference architectures for efficient deployment
• Collaborate with data scientists, product managers, engineers, and business stakeholders in Agile teams
• Debug, optimise, and enhance ML models for quality and performance improvements
• Mentor team members and present technical findings to diverse audiences
• Stay current with AI/GenAI trends and evaluate emerging tools and frameworks

Years of experience required: 7-12 years

Education qualification: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (60% above)

Degrees/Field of Study required: Bachelor of Technology, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

• Snowflake (Platform)

Optional Skills

• Accepting Feedback
• Accepting Feedback
• Active Listening
• AI Fluency
• AI-Human Collaboration
• 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 {+ 46 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements Not Specified

Available for Work Visa Sponsorship? No

Government Clearance Required? No

Job Posting End Date July 23, 2026

Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.