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Tier-1 brand, mid-level generalist AI role, and metro Bangalore increase applicant competition.
Role requires specialized agentic AI and backend engineering skills, limiting cross-industry interchangeability.
Explicit 4–7 years plus many mandatory Java, Kubernetes, Kafka, security, and GenAI skills make filters strict.
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Lead design, development, and deployment of enterprise-grade agentic AI solutions using Java microservices (Spring Boot) and cloud-native architecture.
Develop and integrate AI agents using frameworks like LangChain, LangGraph, and AutoGen, implementing RAG pipelines and prompt engineering.
Build secure, scalable backend services with OAuth2/JWT authentication, observability (OTEL), GitOps deployment (ArgoCD), and resilience patterns on Kubernetes.
4 to 7 years work experience in Java microservices development and cloud-native/Kubernetes environments.
Strong expertise in Java, Spring Boot, OAuth2, JWT, API security, and distributed systems resilience patterns.
Proficiency with Kafka event-driven architectures, observability tools (OTEL, Prometheus, Grafana), and GitOps/CI-CD pipelines.
Bachelor's degree in Engineering or Master's (MBA), exposure to Generative AI including LLMs and RAG pipelines.
Experienced backend engineer with deep skills in agentic AI system development and deployment at enterprise scale.
Hands-on knowledge of cloud-native Kubernetes applications, service mesh (Istio), multi-cloud deployments, and secure microservices.
Familiarity with AI orchestration tools, agentic AI frameworks, GraphQL APIs, NoSQL databases, and integrated full-stack AI solutions.