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Strong employer brand, metro Bengaluru location, mid-level generalist AI/backend role, and broad skillset amplify competition.
Role requires agentic AI, LLM/RAG expertise plus Java microservices, making cross-industry transferability limited.
Explicit 4–7 years plus many mandatory skills (Java, Spring, Kubernetes, GenAI, Kafka) enforces strict shortlisting.
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Lead design, development, and deployment of enterprise-grade agentic AI solutions using Java microservices and cloud-native architectures.
Develop and integrate AI agents with frameworks like LangChain, LangGraph, and implement RAG pipelines and prompt engineering.
Build secure, scalable backend services with Spring Boot, implement OAuth2/JWT security, observability, resilience patterns, and collaborate on scalable AI solutions.
4 to 7 years of relevant work experience in Java microservices and cloud-native backend development.
Strong proficiency in Java, Spring Boot, Kubernetes, OAuth2/JWT, distributed systems, observability tools (OTEL, Prometheus, Grafana), and Kafka event-driven architecture.
Bachelor's degree in Engineering (BE/BTech) or MBA; certifications like AWS Developer/ Solutions Architect or Kubernetes (CKA/CKAD) preferred but not mandatory.
Experience with GenAI fundamentals including LLMs, RAG pipelines, agentic AI, and ReactJS for application layers.
Experienced backend engineer skilled in building secure and resilient cloud-native AI systems using Java microservices and Kubernetes.
Familiar with agentic AI frameworks and generative AI agents, capable of delivering production-ready AI solutions integrating with enterprise platforms.
Comfortable working with modern DevOps practices including GitOps, CI/CD, service mesh, and cloud IAM in multi-cloud environments.