IN_Senior Associate_Agentic Pipeline Engineer _GCC_Advisory_Bangalore

*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

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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. "

• →Design and develop Agentic AI pipelines and workflows using Large Language Models (LLMs). 

• →Build single-agent and multi-agent solutions for complex business use cases. 

• →Develop reusable components for tool calling, orchestration, prompt management, memory, routing, and workflow execution. 

• →Implement RAG (Retrieval-Augmented Generation) pipelines integrating enterprise data sources with LLM applications. 

• →Integrate agents with REST APIs, databases, vector stores, enterprise applications, and external tools. 

• →Build scalable backend services and APIs using Python and frameworks such as FastAPI. 

• →Work with agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent frameworks. 

• →Develop and optimize embedding, retrieval, chunking, reranking, and vector-search pipelines. 

• →Implement appropriate guardrails, validation, error handling, observability, logging, and evaluation for GenAI applications. 

• →Optimize agent workflows for accuracy, latency, reliability, and cost. 

• →Containerize and deploy AI services using Docker and CI/CD practices. 

• →Collaborate with architects, engineering teams, data scientists, and business stakeholders to translate use cases into production-ready Agentic AI solutions. 

• →Perform unit testing, integration testing, troubleshooting, and production support for AI pipelines. 

• Strong programming experience in Python. 

• Hands-on understanding of Generative AI and Large Language Models. 

• Experience developing LLM-based applications and agentic workflows. 

• Knowledge of frameworks such as:  

• LangChain 

• LangGraph 

• Microsoft Semantic Kernel 

• AutoGen or similar agent frameworks 

• Strong understanding of RAG architecture and vector-based retrieval. 

• Experience with Vector Databases / Search, such as FAISS, Pinecone, Weaviate, Chroma, Azure AI Search, or equivalent. 

• Experience integrating REST APIs, databases, and enterprise applications. 

• Knowledge of prompt engineering, tool/function calling, structured outputs, embeddings, and context management. 

• Experience with Git, Docker, CI/CD, and API development. 

• Exposure to at least one major cloud platform such as Azure, AWS, or GCP. 

• Exposure to Internal Developer Platforms (IDP). 

• Experience with service mesh (Istio). 

• Knowledge of multi-cloud deployment (AWS/Azure/GCP). 

• Exposure to agentic UX patterns. 

• Familiarity with AI orchestration tools. 

• Hands-on experience with agentic AI systems in production. 

• Experience with tools like Claude, Cursor. 

• Deep experience with agentic frameworks (LangGraph, CrewAI, etc.). 

• Exposure to full-stack AI applications. 

AWS Developer / Solutions Architect 

Kubernetes Certification (CKA/CKAD), AWS or Azure AI Certifications 

3–7 years of software engineering / AI engineering experience. 

BE / B.Tech / M.Tech / MCA