IN_Senior Associate_AI/Agentic Platform_GCC_Advisory_Hyderabad
Description
Line of Service
Advisory
Industry/Sector
FS X-Sector
Specialism
Operations
Management Level
Senior Associate
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 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
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
Mandatory skill sets
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Python & Frameworks:
Production-level Python: FastAPI (primary), Flask, async patterns ( asyncio , aiohtt p )
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
Promp