IN_Senior Associate_Agentic AI Developer using Python_GCC_Advisory_Bangalore

PwC India; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC India is seeking an experienced Agentic AI Developer to design, build, and deploy autonomous AI agents using Python. You will architect multi-agent workflows, integrating LLMs with real data sources and building the orchestration and reasoning layers that power self-directed AI pipelines.

This role sits at the intersection of AI engineering, backend development, and system design. The position requires strong fundamentals in async programming, API development (FastAPI, REST, streaming), data

Qualifications

• Experience in AI agent design and orchestration.
• Proficiency with Python and async programming.
• Hands-on with LangChain, LangGraph, and AutoGen.
• Familiarity with OpenAI API, Anthropic Claude, and HuggingFace Transformers.
• Development with FastAPI, REST, and streaming APIs.
• Strong data handling with Pandas and structured data parsing.
• Experience with Redis, Kafka, or RabbitMQ for event-driven triggers.
• PostgreSQL for state management; observability with OpenTelemetry.

Responsibilities

• Design and develop autonomous AI agents with multi-step reasoning and inter-agent collaboration.
• Build multi-agent systems with defined roles and inter-agent communication.
• Implement agent orchestration frameworks for workflow coordination.
• Manage agent memory layers and tool-call pipelines to interact with APIs, databases, and external services.
• Integrate LLMs and build robust prompt templates and chain-of-thought strategies.

Skills

Python programming

Async programming

OOP

Design patterns

LangChain

LangGraph

AutoGen

CrewAI

OpenAI API

Anthropic Claude

HuggingFace Transformers

FastAPI

REST

Streaming APIs

Prompt Engineering

CoT

ReAct

Structured outputs

Function calling

Pandas

Data parsing

Redis

Kafka

RabbitMQ

PostgreSQL

LangSmith

OpenTelemetry

Metrics

Education

BE/Btech/MCA/Mtech/MBA

Tools

LLM APIs

Pinecone/Weaviate

Job description

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision‑making and driving business growth.

Those in intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs.

Why PWC

At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes forour 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 foreach other. Learn more about us 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.

Job Summary-

We are looking for an experienced Agentic AI Developer to design, build, and deploy intelligent autonomous agent systems using Python. You will be responsible for architecting multi‑agent workflows, integrating LLMs with real‑world tools and data sources, and building the orchestration and reasoning layers that power self‑directed AI pipelines. This role sits at the intersection of AI engineering, backend development, and system design.

Responsibilities:

Agent Design & Orchestration

• Design and develop autonomous and semi‑autonomous AI agents capable of multi‑step reasoning, planning, and decision‑making
• Build multi‑agent systems with defined roles, inter‑agent communication, and collaborative task execution
• Implement agent orchestration frameworks (LangGraph, AutoGen, CrewAI, or custom‑built) for workflow coordination
• Define and manage agent memory layers - short‑term (context window), long‑term (vector stores), and episodic memory
• Develop tool‑use and function‑calling pipelines enabling agents to interact with APIs, databases, and external services

LLM Integration & Prompt Engineering

• Integrate and fine‑tune interactions with LLM providers (OpenAI, Anthropic, Mistral, open‑source models via HuggingFace)
• Design robust prompt templates, system instructions, and chain‑of‑thought strategies for reliable agent behavior
• Implement RAG (Retrieval‑Augmented Generation) pipelines connecting agents to structured and unstructured knowledge bases
• Manage LLM output validation, structured output parsing, and fallback/retry logic

Backend Services & API Layer

• Build FastAPI‑based microservices to expose agent capabilities as REST/streaming APIs
• Develop event‑driven agent triggers using message queues (Redis Streams, Kafka, RabbitMQ)
• Design agent state management and session persistence using PostgreSQL / Redis
• Implement task queuing, scheduling, and async execution for long‑running agent workflows

Tool & Data Integration

• Build and register custom agent tools for file processing, web search, SQL querying, SFTP operations, and third‑party API calls
• Integrate agents with structured data sources (PostgreSQL, data lakes) and unstructured sources (PDFs, Excel, emails)
• Connect agents to vector databases (Pinecone, Weaviate, pgvector, ChromaDB) for semantic retrieval
• Enable agents to interact with external systems via MCP (Model Context Protocol) or custom tool registries

Guardrails, Safety & Reliability

• Implement guardrails and output validators to ensure agent responses meet business and compliance requirements
• Build human‑in‑the‑loop (HITL) checkpoints for critical decision nodes within agent workflows
• Design agent sandboxing and execution boundaries to prevent unintended actions
• Develop comprehensive error handling, retry strategies, and graceful degradation patterns for agent failures

Observability & Evaluation

• Instrument agents with end‑to‑end tracing (LangSmith, Arize, custom logging) across reasoning steps and tool calls
• Build evaluation pipelines to measure agent accuracy, latency, tool‑use correctness, and goal completion rates
• Define and monitor KPIs for agent performance - task success rate, hallucination rate, escalation frequency
• Maintain audit logs of agent decisions, tool invocations, and LLM interactions for debugging and compliance

Mandatory skill sets:

Programming Python (advanced) - async programming, OOP, design patterns Agent Frameworks LangChain, LangGraph, AutoGen, CrewAI, or equivalent LLM APIs OpenAI API, Anthropic Claude, HuggingFace Transformers API Development FastAPI, REST, Streaming APIs (SSE / WebSockets) Prompt Engineering CoT, ReAct, structured outputs, function calling Data Handling Pandas, structured/unstructured data parsing Messaging & Events Redis, Kafka, or RabbitMQ for event‑driven agent triggers Databases PostgreSQL for state/session management Observability Logging, tracing (LangSmith / OpenTelemetry), metrics

Preferred skill sets:

Experience with fine‑tuning or RLHF pipelines for domain‑specific LLMs • Familiarity with Model Context Protocol (MCP) for standardized tool integration • Knowledge of open‑source LLM deployment (Ollama, vLLM, LiteLLM) • Exposure to Kubernetes‑based microservice deployment for agent services • Background in data engineering or ingestion platforms complementing agent data access • Understanding of AI safety principles, responsible AI, and model risk management • Experience with browser‑use or computer‑use agents for UI automation tasks

Years of experience required :

4-7

Education qualification:

BE/Btech/MCA/Mtech/MBA