Agentic AI Developer

PriceWaterhouseCoopers Pvt Ltd ( PWC ); Bengaluru; On-site; INR 900,000 - 1,600,000; Full time

Benefits offered by this job

Inclusive benefits

Flexibility programmes

Mentorship

Job summary

PricewaterhouseCoopers Pvt Ltd in Bengaluru seeks an experienced Agentic AI Developer to design, build, and deploy intelligent autonomous agent systems using Python. You will architect multi-agent workflows, integrate LLMs with real-world tools, and power self-directed AI pipelines across a combined AI engineering and backend systems role.

The position emphasizes orchestration, tool-use pipelines, and robust safety rails, with exposure to FastAPI, REST/Streaming APIs, and vector databases.

Qualifications

• Experience designing autonomous AI agents capable of multi-step reasoning.
• Proficient in structuring multi-agent workflows and tool integration.
• Strong background in Python, async programming, and backend services.

Responsibilities

• Design and develop autonomous AI agents with multi-step reasoning and collaboration.
• Build multi-agent systems with defined roles and inter-agent communication.
• Implement agent orchestration frameworks for workflow coordination.
• Develop tools to interact with APIs, databases, and external services.

Skills

Python programming

LLM integration

API development

Prompt engineering

Data handling

Messaging & events

PostgreSQL/ Redis

Observability/logging

Education

Bachelor's degree in Computer Science / IT

Tools

LangChain

LangGraph

AutoGen

CrewAI

OpenAI API

HuggingFace Transformers

FastAPI

REST/Streaming APIs

Job description

IN_Manager_ Agentic AI Developer_GCC_Advisory_Bangalore Line of Service Advisory Industry/Sector FS X-Sector Specialism Operations Management Level Manager 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 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 .

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 Description & 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-build) 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

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

Experience Years of experience required

• 3+ years of overall software/data/AI engineering experience
• 1-2 years of hands-on experience building LLM-based applications or AI agent systems
• Demonstrated experience shipping production-grade agentic workflows - not just prototypes

Education qualification

Bachelor's degree in Computer Science , Information Technology, or a related field .

Degrees/Field of Study required

Master of Engineering, Bachelor of EngineeringDegrees/Field of Study preferred:

Certifications

(if blank, certifications not specified)

Required Skills

Web UI Development Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, Analytical Thinking, Automation Algorithms, Automation Engineering, Automation Framework Design and Development, Automation Programming, Automation Solutions, Automation Studio, Automation System Efficiency, Blue Prism, Business Analysis, Business Performance Management, Business Process Analysis, Business Process Automation (BPA), Business Transformation, Business Value Optimization, C++ Programming Language, Coaching and Feedback, Cognitive Automation, Communication, Conducting Discovery, Configuration Management (CM) {+ 41 more}

Desired Languages

(If blank, desired languages not specified)

Travel Requirements Not Specified

Available for Work Visa Sponsorship? No

Government Clearance Required? No

Job Posting End Date September 15, 2026

Experience Level Mid Level