IN_Senior Associate_Agentic AI Engineer_GCC_Advisory_Bangalore

PwC International

Bengaluru

On-site

INR 1,200,000 - 1,800,000

Full time

8 days ago

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Benefits offered by this job

Mentorship

Flexible working arrangements

Job summary

PwC Bengaluru is seeking a Senior Associate to drive enterprise-grade AI-enabled solutions. You will design and develop agentic AI systems built on Java microservices, leverage cloud-native Kubernetes, and implement secure APIs, OAuth2/JWT, and scalable backend architectures.

You will collaborate across teams to deploy RAG pipelines, observability, and GitOps-driven workflows, while applying GenAI fundamentals and React-based front-end layers. 4–8 years experience required.

Qualifications

Strong Java and Spring Boot microservices development experience.
Experience building cloud-native applications on Kubernetes.
Hands-on experience with OAuth2, JWT, and secure API development.
Deep knowledge of distributed systems and resilience patterns.
Strong experience with observability tools (OTEL, Prometheus, Grafana).
Strong experience with Kafka-based event-driven architecture.
Hands-on with GitOps, CI/CD pipelines, and container platforms.
Proficiency in GraphQL API design and development.
Understanding of GenAI fundamentals including LLMs, RAG pipelines, and agentic AI landscape.
Experience with ReactJS for integrated application layers.
NoSQL databases (MongoDB, DynamoDB).
Certifications (AWS/Azure/GCP AI) preferred.

Responsibilities

Design and build agentic AI systems integrated with enterprise Java microservices.
Develop and deploy AI agents using LangChain, LangGraph, Bedrock Agents, AutoGen, or CrewAI.
Implement RAG pipelines, prompt engineering techniques, and evaluation frameworks.
Build secure, scalable APIs and backend services using Spring Boot and IDP.
Implement OAuth 2.0, JWT-based authentication, and secure service-to-service identity.
Architect Kubernetes-native applications following 12-Factor principles.
Enable observability using OpenTelemetry, logging, tracing, and metrics.
Design centralized configuration and secrets management using HashiCorp Vault or AWS Secrets Manager.
Implement GitOps-based deployment strategies using ArgoCD.
Build resilient systems using retries, circuit breakers (Resilience4j).
Implement API security and authorization using RBAC and ABAC models.
Work with service mesh technologies such as Istio.
Integrate cloud IAM and Kubernetes workload identity.
Develop event-driven systems using Apache Kafka.
Collaborate with teams to deliver scalable AI solutions.

Skills

Java Spring Boot

Kubernetes

OAuth2/JWT

Distributed systems

Observability (OTEL)

Kafka

GitOps/CI-CD

GraphQL

ReactJS

NoSQL (MongoDB/DynamoDB)

Education

BE/BTech

MCA

MTech

MBA

Tools

Spring Boot

Kubernetes

JWT/OAuth2

GraphQL

ReactJS

Kafka

CI/CD

GitOps

MongoDB

DynamoDB

Job 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.

Role Summary

Drive the design, development, and deployment of enterprise-grade agentic AI solutions built on a strong foundation of Java microservices, cloud-native architecture, and secure, scalable platforms. The role blends Agentic AI engineering with modern backend engineering practices to deliver production-ready, resilient, and governed AI systems, along with the ability to contribute to end-to-end application layers.

Responsibilities

Design and build agentic AI systems integrated with enterprise Java microservices (Spring Boot-based architectures).
Develop and deploy AI agents using frameworks such as LangChain, LangGraph, Bedrock Agents, AutoGen, or CrewAI.
Implement RAG pipelines, prompt engineering techniques, and evaluation frameworks.
Build secure, scalable APIs and backend services using Spring Boot and opinionated Internal Developer Platforms (IDP).
Implement OAuth 2.0, JWT-based authentication, and secure service-to-service identity.
Architect Kubernetes-native applications following 12-Factor principles.
Enable observability using OpenTelemetry (OTEL), logging, tracing, and metrics.
Design centralized configuration and secrets management using HashiCorp Vault or AWS Secrets Manager.
Implement GitOps-based deployment strategies using tools such as ArgoCD.
Build resilient systems using retries, circuit breakers (Resilience4j).
Implement API security and authorization using RBAC and ABAC models.
Work with service mesh technologies such as Istio.
Integrate cloud IAM and Kubernetes workload identity.
Develop event-driven systems using Apache Kafka.
Collaborate with teams to deliver scalable AI solutions.

Mandatory Skill sets

Strong Java and Spring Boot microservices development experience.
Experience in building cloud-native applications on Kubernetes.
Hands-on experience with OAuth2, JWT, and secure API development.
Deep knowledge of distributed systems and resilience patterns.
Strong experience with observability tools (OTEL, Prometheus, Grafana).
Strong experience with Kafka-based event-driven architecture.
Hands-on with GitOps, CI/CD pipelines, and container platforms.
Proficiency in GraphQL API design and development.
Understanding of GenAI fundamentals including LLMs, RAG pipelines, and agentic AI landscape.
Experience with ReactJS for integrated application layers.
Hands-on experience with NoSQL databases (MongoDB, DynamoDB, etc.).
Certifications (Preferred) AWS Developer / Solutions Architect Kubernetes Certification (CKA/CKAD), AWS or Azure AI Certifications.

Preferred Skill sets