Description

• 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 patterns like retries, circuit breakers (Resilience4j).
• Implement API security and authorization using RBAC and ABAC models.
• Work with service mesh technologies such as Istio for traffic management and security.
• Integrate cloud IAM (AWS IAM) and Kubernetes workload identity (IRSA).
• Develop event-driven systems using Apache Kafka and schema registry patterns.
• Collaborate with product teams, architects, and platform engineers to deliver scalable AI solutions.

Qualifications:
Must-Have Skills:

• Strong Java and Spring Boot microservices development experience.
• Experience in ReactJS
• Experience in building cloud-native applications on Kubernetes.
• Hands-on experience with OAuth2, JWT, secure API development.
• Deep knowledge of distributed systems, fault tolerance, 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, including schema design, query optimization, and integration with microservices.
• Understanding RAG pipelines, embeddings, and vector databases.
• Experience with agentic AI frameworks and LLM-based systems.

Good-to-Have Skills:

• Exposure to Internal Developer Platforms (IDP) and platform engineering.
• Experience with service mesh (Istio) and advanced networking.
• Knowledge of multi-cloud deployment (AWS/Azure/GCP).
• Exposure agentic UX patterns and conversational APIs.
• Familiarity with AI orchestration tools (Azure AI Foundry, Vertex AI, Bedrock).
• Exposure to agentic productivity tools (e.g., Cursor, Claude-based tooling, Augment Code) is an advantage.

Certifications (Preferred):

• AWS Developer / Solutions Architect
• Kubernetes Certification (CKA/CKAD)
• AWS or Azure AI Certifications

Key Skills

Education

Bachelor's degree