IN_Senior Associate_AI Engineer (Java Microservices Focus) _GCC_Advisory_Bangalore

Job Description & 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.).

Preferred Skill sets

• Exposure to Internal Developer Platforms (IDP).

• Experience with service mesh (Istio).

• Knowledge of multi-cloud deployment (AWS/Azure/GCP).

• Exposure to agentic UX patterns.

• Familiarity with AI orchestration tools.

• Hands-on experience with agentic AI systems in production.

• Experience with tools like Claude, Cursor.

• Deep experience with agentic frameworks (LangGraph, CrewAI, etc.).

• Exposure to full-stack AI applications.

Certifications (Preferred)

AWS Developer / Solutions Architect

Kubernetes Certification (CKA/CKAD), AWS or Azure AI Certifications