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Strong employer brand, metro location, popular mid-level AI title, and broad backend requirements increase competition.
AI plus Java microservices emphasis reduces cross-industry transferability somewhat, hence medium sensitivity.
Explicit 4–7 years plus many mandatory technical skills increases shortlisting rigidity.
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Design, develop, and deploy enterprise-grade agentic AI solutions using Java microservices and cloud-native architectures.
Develop AI agents with frameworks like LangChain and implement RAG pipelines, prompt engineering, and evaluation.
Build secure, scalable backend services and APIs with OAuth2/JWT authentication, Kubernetes-native applications, and observability tools, integrating event-driven systems like Kafka.
4 to 7 years of relevant work experience.
Strong Java and Spring Boot microservices development expertise.
Experience in building cloud-native applications on Kubernetes with OAuth2, JWT, and secure API development.
Bachelor's degree in Engineering (BE/BTech) or MBA (Master of Business Administration).
Experienced in distributed systems with resilience patterns and observability tooling (OTEL, Prometheus, Grafana).
Proficient with event-driven architectures using Apache Kafka and GitOps CI/CD pipelines.
Knowledgeable in Generative AI agents, agentic AI frameworks (e.g., LangGraph, CrewAI), and integration of AI with microservices backend systems.