Industry/Sector

Specialism

Management Level

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a Generative AI-Data Scientist-Senior Associate, you will leverage advanced analytics and statistical techniques to transform raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Data and Analytics Engineering practice, you will focus on exploratory and descriptive analysis, statistical modeling, and creating data visualizations to solve complex business problems and inform strategic decisions. As a Senior Associate, you will build meaningful client connections, manage and inspire others, and navigate increasingly complex situations to grow your personal brand and deepen your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality solutions even when the path forward isn’t clear.

In this role at PwC Acceleration Center India, you will respond effectively to diverse perspectives, use a broad range of tools and methodologies to generate new ideas, and interpret data to inform insights and recommendations. You will uphold professional and technical standards, developing a deeper understanding of the business context and how it is changing. This position offers the opportunity to embrace increased ambiguity, ask questions, and use these moments as opportunities for growth.

Responsibilities

- Develop and implement agentic AI systems — including tool-calling, autonomous task planning and execution, multi-step reasoning workflows, agent memory management, and human-in-the-loop escalation mechanisms for complex enterprise use cases. Leverage Agentic frameworks like LangGraph, CrewAI, Autogen, cloud-based frameworks, etc.

- Develop and deploy agentic AI solutions using any of the cloud-native services as per defined requirement (Azure AI Foundry, AWS Bedrock Agents, GCP Vertex AI Agent Builder, etc.), and associated cloud services for scalable agent execution.

- Implement and maintain evaluation frameworks for agentic AI solutions — assessing agent reasoning, tool-use reliability, multi-step task completion, hallucination risk, and autonomous decision quality to ensure production readiness and continuous performance improvement.

- Design, develop, and optimize RAG pipelines end-to-end (using LangChain, LlamaIndex, etc.) — including chunking strategies, embedding model selection, integrate production-grade vector databases (Pinecone, Weaviate, OpenSearch, Azure AI Search, etc.), hybrid retrieval, re-ranking.

= Design, develop, and optimize prompt engineering strategies, including prompt chaining, few-shot/zero-shot techniques, and prompt templating, to enhance the accuracy, reliability, and consistency of LLM-powered applications and agentic workflows.

- Collaborate with cross-functional teams (client managers, data scientists, architects, DevOps engineers) to translate business requirements into technical implementations — ensuring alignment with solution architecture defined by the lead architects.

- Implement and uphold Python development best practices during implementation.

- Monitor solution performance, track key metrics, test all affected scenarios and proactively adjust implementations — identifying issues in accuracy, latency, throughput, and cost, and applying optimizations at the code and infrastructure level.

- Communicate technical findings, implementation progress, and insights to stakeholders — contributing to documentation, sprint demos, and knowledge-sharing within the team

What You Must Have

- At least a Bachelor's & Master's degree
- At least 2 years of experience
- Oral and written proficiency in English required

What Sets You Apart

- Proven experience building and deploying production-grade Agentic AI solutions using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.

- Strong knowledge of AI interoperability protocols (e.g., MCP, A2A) and advanced Retrieval

- Augmented Generation (RAG) architectures such as Graph RAG, Vectorless RAG, and Hybrid RAG.

- Deep understanding of traditional AI/ML fundamentals including model building, fine-tuning, quantization, feature engineering, and model evaluation.

- Foundational awareness of Responsible AI principles, security practices for safe deployments, and experience evaluating GenAI and Agentic AI applications.

- Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), familiarity with CI/CD pipelines, and relevant AI/GenAI certifications preferred.

Travel Requirements

Job Posting End Date