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PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

Agentic Pipeline Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 3 years of software engineering or AI engineering experience, with 3–7 years specified in the mandatory qualifications.
  • Strong programming experience in Python.
  • Hands-on understanding of Generative AI and Large Language Models.
  • Experience developing LLM-based applications and agentic workflows.
  • Strong understanding of Retrieval-Augmented Generation architecture and vector-based retrieval.
  • Experience with vector databases or search, such as FAISS, Pinecone, Weaviate, Chroma, or Azure AI Search.
  • Experience integrating REST APIs, databases, and enterprise applications.
  • Knowledge of prompt engineering, tool or function calling, structured outputs, embeddings, and context management.
  • A Bachelor's degree in Computer Science, Engineering, or a related field is required. The education section also lists Bachelor of Engineering and Master of Engineering as required fields of study.

Responsibilities

  • Design and develop Agentic AI pipelines and workflows using Large Language Models.
  • 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 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.
  • Develop and optimize embedding, retrieval, chunking, reranking, and vector-search pipelines.
  • Implement guardrails, validation, error handling, observability, logging, and evaluation for Generative AI 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.

Desired Qualifications

  • Knowledge of agent frameworks such as LangGraph, Microsoft Semantic Kernel, and AutoGen or similar frameworks.
  • Experience with Git, Docker, CI/CD, and API development.
  • Exposure to at least one major cloud platform such as Azure, AWS, or GCP.

About the Company

PricewaterhouseCoopers (PwC)

Global professional services: assurance, tax, consulting

PwC provides assurance (audit), tax, legal services, consulting and deals advisory to organisations worldwide. It uses multidisciplinary teams across accounting, advisory, technology and industry, delivered through a global network of locally established firms that collaborate with technology partners to offer AI, cloud, managed services and digital trust. PwC differentiates itself with an integrated, global-local service model and technology-enabled offerings that address complex client needs across risk, transformation, reporting and sustainability. Its goal is to help clients improve governance, efficiency and value by supporting reporting accuracy, business transformation, risk management and sustainable practices.

Company size
10,001+
Company stage
Early VC
Total funding
$3.3M
Headquarters
London, United Kingdom
Founded
1989

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