23d ago

IN_Senior Associate_AI/Agentic Platform_GCC_Advisory_Hyderabad

Hyderabad - Salarpuriasenior

OtherAssociate

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Quick Summary

Key Responsibilities

1. Multi-Cloud Architecture & Implementation Design and architect scalable,

Requirements Summary

5–8 years of proven cloud engineering with advanced architectural skills across Azure and/or AWS Python-first engineer: you build agents, pipelines,

Technical Tools

OtherAssociate

Advisory

FS X-Sector

Operations

Senior Associate

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 seeking an experienced Agentic Platform Engineer with strong hyperscaler cloud engineering skills and deep Python expertise to design, develop, and deploy intelligent agentic systems across PGC's multi-cloud, multi-platform estate. Unlike a single-cloud specialist role, this position demands genuine platform agnosticism — you will build agents that span Azure AI, Oracle Agentic Studio, and open-source Python frameworks, integrating with Oracle ERP/HCM, Pega, and ServiceNow as PGC transitions from UiPath RPA to next-generation autonomous agent architectures.

Responsibilities

~3 min read

1. Multi-Cloud Architecture & Implementation

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Design and architect scalable, cloud-native solutions on Azure (primary) and AWS (secondary)

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Implement microservices and serverless architectures: Azure Functions / AWS Lambda, API Gateway, Container Instances

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Deploy and manage containerized workloads using Docker, Kubernetes (AKS / EKS), and Helm

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Design event-driven, async architectures using cloud messaging services (Azure Event Hub, AWS SQS/SNS, Apache Kafka)

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Implement IaC using Terraform (primary) or CloudFormation/ARM for repeatable, auditable deployments

2. Agentic AI Solutions Development

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Design and build intelligent agentic systems that automate multi-step workflows and autonomous decision-making

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Architect and implement multi-agent systems: task decomposition, specialist sub-agents, orchestrator/supervisor patterns, swarm coordination

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Implement RAG (Retrieval-Augmented Generation) pipelines: document ingestion, chunking, embedding, vector retrieval, re-ranking, response synthesis

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Integrate and abstract multiple LLM providers: Azure OpenAI, OpenAI, Anthropic Claude, in a provider-agnostic pattern

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Design structured output and function/tool calling patterns for reliable agent-to-system interactions

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Build agent memory architectures: short-term (in-context), long-term (vector store / relational), episodic (session history)

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Evaluate agent and LLM quality: implement RAGAS, LangSmith, PromptFlow, or custom evaluation harnesses in CI/CD

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Apply prompt engineering best practices: chain-of-thought, structured prompting, output constraints, guardrails

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Implement agentic workflows using LangChain, AutoGen, CrewAI, or similar — with a view to platform-specific integration (Oracle Agentic Studio, Semantic Kernel)

3. Cross-Platform Enterprise Integration

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Build integrations between agentic systems and Oracle ERP/HCM, Pega, and ServiceNow platforms via REST APIs, webhooks, and event streams

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Understand and guide RPA-to-Agentic process migration: redesigning UiPath / RPA workflows as autonomous, intelligent agents

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Manage vector databases and knowledge store integrations: Pinecone, Chroma, Weaviate, pgvector, Azure AI Search

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Design API gateway patterns to route agent invocations across heterogeneous enterprise systems

4. Backend Development with Python

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Develop robust production backend services using Python and FastAPI (primary); Flask for lightweight APIs

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Build RESTful and event-driven APIs with async/await patterns (asyncio, aiohttp)

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Implement SQL and NoSQL database solutions optimized for agentic workloads (query performance, vector indexing)

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Write clean, tested, and documented code — pytest coverage, type hints, linting (ruff, mypy), CI enforcement

5. DevOps & Infrastructure

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Set up and maintain CI/CD pipelines with agent evaluation gates (Azure DevOps, GitHub Actions)

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Monitor, log, and optimize cloud infrastructure and agent system performance

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Manage secrets, RBAC, and HIPAA-aligned security compliance across cloud environments

6. Collaboration & Delivery

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Work with PGC healthcare stakeholders, domain SMEs, and cross-functional delivery teams

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Mentor junior engineers and support cross-skilling of UiPath engineers to Agentic AI delivery

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Document architecture decisions, agent design patterns, and solution specifications

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Contribute to discovery, ROI modelling, and business case development for new agentic use cases

Python & Frameworks:
Production-level Python: FastAPI (primary), Flask, async patterns (asyncio, aiohttp)
Code quality: pytest, type hints, ruff/mypy, dependency management (Poetry or pip-tools)
API design: RESTful best practices, versioning, OpenAPI/Swagger documentation

Hyperscaler & Cloud Services:
Azure (primary): Functions, App Service, AKS, API Management, Event Hub, Service Bus, Cosmos DB, Azure SQL, Azure Storage, Azure Monitor
AWS (secondary): Lambda, API Gateway, EKS, RDS, DynamoDB, S3, SQS/SNS, IAM
Oracle Cloud Infrastructure (OCI): awareness of OCI compute, OCI AI Services — not required at depth but expected familiarity
Docker, Kubernetes (AKS/EKS), Helm, container registries
Terraform (primary IaC); CloudFormation or ARM/Bicep as secondary

Agentic AI & LLM Engineering:
Agentic frameworks: LangChain, AutoGen, CrewAI — production-level usage, not just tutorials
Oracle Agentic Studio: experience or strong willingness to be trained (critical for PGC delivery)
Semantic Kernel: familiarity a plus for Azure-aligned agent orchestration
LLM providers: Azure OpenAI (primary), OpenAI API, Anthropic Claude — provider-agnostic abstraction patterns
RAG pipelines: end-to-end design, embedding model selection, chunking, retrieval, response synthesis, evaluation
Vector databases: Pinecone, Chroma, Weaviate, pgvector, Azure AI Search — schema design, metadata filtering, hybrid search
LLM evaluation: RAGAS, LangSmith, PromptFlow, or custom evaluation harnesses
Multi-agent patterns: supervisor/worker, task delegation, inter-agent messaging, shared state
Structured output and tool/function calling: JSON mode, Pydantic models, tool schema definition
Agent memory: context window management, vector-based long-term retrieval, episodic session storage
Prompt engineering: chain-of-thought, structured prompts, guardrails, output constraints

Database & Storage:
SQL: Azure SQL / PostgreSQL — query optimization, indexing, partitioning
NoSQL: Azure Cosmos DB, DynamoDB — partition key strategy, TTL, read/write throughput
Vector store design for RAG: schema, metadata, hybrid (keyword + vector) search

Healthcare & Compliance Context (Preferred):
HIPAA compliance awareness in cloud architecture (PHI handling, audit logging, encryption at rest/transit)
HL7/FHIR API familiarity for healthcare data exchange
Basic understanding of healthcare operations: revenue cycle, claims, HR, procurement — the domains agents will automate
RPA-to-Agentic migration: understanding of process redesign from UiPath/RPA to agentic patterns

Nice to Have

~1 min read

Node.js / Express.js (2+ years) — useful for lightweight API gateway or webhook integration work
Pega Platform integration experience (decision strategies, case management APIs)
ServiceNow Now Platform integration (Flow Designer, REST APIs, Now Assist/Virtual Agent)
Oracle Agentic Studio production experience (strong differentiator for this engagement)
AWS Bedrock, AWS SageMaker, or Google Vertex AI familiarity (secondary cloud AI services)
Kafka / event streaming experience for real-time agent trigger architectures
Azure certifications: AZ-305, AI-102; or AWS certifications: SAA-C03, MLS-C01
Healthcare GCC or BPO delivery background

Agentic Platforms

5–8 years of proven cloud engineering with advanced architectural skills across Azure and/or AWS
Python-first engineer: you build agents, pipelines, and APIs in Python by default
3+ years hands-on Agentic AI delivery — production RAG pipelines, multi-agent systems, LLM evaluation — not just experimentation
Genuine platform agnosticism: you can integrate agents across Oracle, Azure, Pega, and ServiceNow without being married to one cloud
RAG and vector database fluency — you have designed, tuned, and evaluated a RAG system in production
Appetite to learn Oracle Agentic Studio — PGC's primary agentic orchestration platform is Oracle-stack, and you must be willing to master it
Healthcare curiosity — you care about the operational problems being solved, not just the tech
Leader mindset: can independently architect solutions, guide cross-skilling engineers, and drive end-to-end delivery

Requirements

~1 min read

5–8 years of proven cloud engineering with advanced architectural skills across Azure and/or AWS
Python-first engineer: you build agents, pipelines, and APIs in Python by default
3+ years hands-on Agentic AI delivery — production RAG pipelines, multi-agent systems, LLM evaluation — not just experimentation
Genuine platform agnosticism: you can integrate agents across Oracle, Azure, Pega, and ServiceNow without being married to one cloud
RAG and vector database fluency — you have designed, tuned, and evaluated a RAG system in production
Appetite to learn Oracle Agentic Studio — PGC's primary agentic orchestration platform is Oracle-stack, and you must be willing to master it
Healthcare curiosity — you care about the operational problems being solved, not just the tech
Leader mindset: can independently architect solutions, guide cross-skilling engineers, and drive end-to-end delivery

Accepting Feedback, Accepting Feedback, Active Listening, Agile Methodology, AI Fluency, AI-Human Collaboration, 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, Cognitive Automation, Communication, Conducting Discovery {+ 39 more}

September 18, 2026