Backend & AI Engineering (Python/LLM/RAG) - Senior 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 & AI Engineering (Python/LLM/RAG) - Senior Associate, you will be at the forefront of developing innovative software solutions to drive digital transformation and enhance business performance. Within our Advisory - Other practice, you will combine technical experience with creative thinking to deliver software products that revolutionize industries and provide exceptional user experiences. In this role, you will design, code, and test applications that meet the evolving needs of clients. As a Senior Associate, you will focus on building meaningful client connections and learning how to manage and inspire others. You will navigate increasingly complex situations, growing your personal brand and deepening your technical skills. You are expected to anticipate the needs of your teams and clients, delivering quality work even when the path forward isn’t clear. This role at PwC Acceleration Center India offers the opportunity to use a broad range of tools and methodologies to generate new ideas and solve problems, while upholding professional and technical standards. Embrace the chance to develop a deeper understanding of the business context and how it is changing, using these moments as opportunities to grow. Responsibilities - Developing innovative software solutions to drive digital transformation and enhance business performance - Designing, 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. - Applying technical skills in Python to create efficient backend systems and AI-driven 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. You will also help advance an 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.

-Working with LLM evaluation frameworks such as Azure AI Evaluations, DeepEval. What You Must Have

4+ years of 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 building production LLM applications, RAG solutions, and AI agents.

Experience designing and optimizing multi-agent workflows using frameworks such as LangChain, LangGraph, or DeepAgents, including tool-calling and agent routing.

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.