Full Stack Python - Experienced Associate

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 Backend Engineering (Python) - Associate, you will be at the forefront of developing innovative software solutions that drive digital transformation and enhance business performance. Within our Advisory practice, you will focus on designing, coding, and testing applications that transform industries and deliver exceptional user experiences. As an Associate, you will contribute to client engagement and projects while developing your skills and knowledge to deliver quality work.

You will be exposed to clients to learn how to build meaningful connections, manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources.

In this role at PwC Acceleration Center India, you will apply your learning mindset and take ownership of your development, appreciating diverse perspectives and actively listening to express ideas clearly. You will gather information from various sources to analyze facts and discern patterns, committing to understanding how the business works and building commercial awareness. This position offers a dynamic environment where every experience is an opportunity to learn and grow, allowing you to navigate through the firm and open doors to more opportunities.

Responsibilities

• Designing and building the core intelligence and services layer of AI-powered enterprise applications.
• Developing scalable, asynchronous backend services (e.g., FastAPI) while building and owning multi-agent LLM pipelines that power capabilities such as document analysis, content generation, and Retrieval-Augmented Generation (RAG)-based Q&A within clean, modular Python codebases.
• Hands-on experience building both traditional backend services and LLM-powered applications.
• working closely with frontend, AI, and quality engineering teams across one or more product pods to design, implement, and scale agentic workflows, RAG pipelines, and the supporting data and job-processing infrastructure.
• Advancing agent-driven, specification-led development lifecycle with appropriate human approval gates.
• working with agentic AI frameworks (e.g., LangChain, LangGraph, DeepAgents), vector databases, prompt engineering, and AI-assisted development tools such as Cursor and GitHub Copilot is highly desirable.
• working with LLM evaluation frameworks such as Azure AI Evaluations, DeepEval, or similar tools is also a strong plus.

What You Must Have

• Strong experience in backend software engineering with deep Python expertise, including async/await and asyncio.
• Hands-on experience building production services using FastAPI or similar modern asynchronous frameworks.
• Proficiency with SQL and SQLAlchemy 2.0, including relational data modeling.
• Experience designing modular, layered architectures (domain, application, infrastructure) using Clean Architecture and dependency injection principles.
• Hands-on experience building LLM-powered applications and RAG pipelines, including ingestion, chunking, embeddings, and vector search.
• Experience working with CI/CD pipelines and containerized environments (Docker).
• Strong analytical, debugging, and problem-solving skills.

What Sets You Apart

• Experience designing and optimizing multi-agent workflows using frameworks such as LangChain, LangGraph, or DeepAgents, including tool-calling and agent routing.
• Experience building production LLM applications, RAG solutions, and AI agents.
• Experience with vector databases (e.g., ChromaDB) and optimizing retrieval quality, latency, and cost.
• Familiarity with Azure services such as Azure Service Bus, Blob Storage, and message-driven/background processing.
• Exposure to Cursor, GitHub Copilot, GitHub Remote Agents, or similar AI-assisted development tools.
• Familiarity with LLM observability and evaluation tools such as Langfuse, Azure AI Evaluations, DeepEval, or RAG evaluation techniques.
• Interest in Specification-Driven Development (SDD), autonomous software delivery, and human-in-the-loop governance.
• Experience working in finance, tax, legal, or other regulated, document-intensive domains.