AI/ML Computational Science Manager

Role Overview

As an AI/ML Computational Science Manager at PwC in Hyderabad, you will lead the creation of cutting-edge data-driven solutions that convert raw information into strategic insights. Your leadership will encompass spearheading data science teams to implement sophisticated analytics, machine learning, and artificial intelligence within decision-making workflows.

Key Responsibilities

• Direct design and development of advanced data solutions transforming raw data into actionable intelligence.
• Guide teams to apply statistical and advanced analytic methods for making data-informed decisions.
• Harness machine learning and AI techniques to optimize data science processes and predictive modeling.
• Create and oversee scalable data pipelines and data lakes that facilitate complex analytics.
• Lead the development of data visualizations aimed at addressing intricate business challenges and strategic planning.
• Collaborate closely with client stakeholders to discover opportunities for data-driven innovation and growth.
• Mentor team members to enhance their expertise in data science and analytics disciplines.
• Ensure data integrity and quality within analytics frameworks through validation mechanisms.
• Promote the adoption of pioneering technologies and advanced practices in data engineering.
• Manage and resolve conflicts or issues involving clients and teams to keep projects on schedule and meet deliverables.

Required Qualifications and Experience

• Holding both a Bachelor's and Master's degree is mandatory.
• A minimum of eight years' professional experience in relevant fields.
• Proficiency in English, both written and spoken, is necessary.

Preferred Expertise and Distinguishing Skills

• More than three years developing and scaling Generative AI projects from conceptual prototypes to enterprise production environments, focusing on performance, cost, latency, and global deployments.
• Proven skills implementing AI interoperability standards such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication at scale for seamless integration.
• Experience with leading cloud AI platforms including Azure AI Foundry, Amazon Bedrock, and Google Vertex AI for deploying agentic AI solutions in production.
• Advanced proficiency in Python programming coupled with practical use of agentic AI frameworks like LangChain, LangGraph, CrewAI, and AutoGen to develop resilient generative AI applications.
• Deep knowledge of sophisticated Retrieval-Augmented Generation (RAG) architectures—Graph RAG, Vectorless RAG, Hybrid RAG—and foundational AI/ML techniques including model creation, fine-tuning, and evaluation.
• Awareness of large language model (LLM) security risks including prompt injections, jailbreaking, data leaks, and misuse of tools, with experience designing layered defense strategies in agentic system architectures.
• Competency in containerization and cloud-native orchestration technologies such as Kubernetes, Docker, and serverless architectures, alongside event-driven designs to deploy scalable AI workloads; holding relevant AI or solution architecture certifications.