IN_Manager_AI/ML Engineer_GCC_Advisory_Bangalore

PwC International; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

PwC in Bengaluru seeks a Senior AI/ML Engineer to design, build, and deploy scalable ML, GenAI, and Agentic AI systems across cloud environments with a focus on productionization and business impact.

You will work on demand forecasting, RAG-based apps, autonomous multi-agent systems, and enterprise AI integration, collaborating in Agile teams to deliver real value.

Qualifications

• Build end-to-end ML/AI pipelines from data to deployment and monitoring.
• Develop and deploy ML, DL, NLP, and GenAI models in production environments.
• Design RAG systems with retrieval, embeddings, and vector search.
• Create Agentic AI solutions with autonomous agents and memory.
• Build and optimize time series forecasting models for demand planning.
• Implement MLOps pipelines including CI/CD and monitoring.
• Ensure models are performant, cost-efficient, and low-latency.
• Integrate AI systems with enterprise APIs and data platforms.
• Design scalable LLM inference architectures for production use.
• Collaborate with cross-functional teams in Agile environments.
• Debug, optimize, and improve ML models; mentor teammates.
• Stay updated on AI/GenAI trends and new tools.

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.

Skills

End-to-end ML/AI pipelines

ML DL NLP GenAI models

RAG systems design

Agentic AI solutions

Time series forecasting

MLOps pipelines

Performance optimization

Enterprise API integration

LLM inference architectures

Agile collaboration

Model debugging & tuning

Mentoring & presenting

AI/GenAI trend awareness

Education

Bachelor’s or Master’s in CS/Engineering

Tools

Java Selenium

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

We’re looking for a Senior AI/ML Engineer who can design, build, and deploy scalable ML, GenAI, and Agentic AI systems across cloud environments with strong focus on productionization, automation, and business impact. You'll work across demand forecasting, RAG-based intelligent applications, autonomous multi-agent systems, and enterprise AI integration.

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

Master of Engineering, Bachelor of Engineering

Degrees/Field of Study preferred

Degrees/Field of Study preferred: Certifications (if blank, certifications not specified)

Required Skills

• Java Selenium, Java Testing

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

• Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship? No

No

Government Clearance Required? No

No

Job Posting End Date

July 22, 2026

Are you ready to make a difference?

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.