What are the responsibilities and job description for the Core Java & AI/LLM Engineer with Devops position at Saransh Inc?
Key Responsibilities
Develop and maintain backend services using Core Java and Spring Boot.
Integrate AI/LLM workflows into Java applications using frameworks like Spring AI.
Design and consume RESTful APIs; familiarity with SOAP/WSDL/XML is a plus.
Build and support event-driven systems using Kafka, JMS, and other messaging platforms.
Collaborate on frontend development using frameworks such as React, Angular, or Vue.
Implement observability tools for logging, metrics, and tracing.
Contribute to CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
Apply clean architecture principles and design patterns in system design.
Participate in technical discussions, mentor team members, and collaborate across teams.
Skill Metrics
Restful APIs
Docker
Kubernetes
Ai/LLM
Java
Spring Boot
Required Skills
7–10 years of experience in Java development and Spring ecosystem.
Experience with AI/LLM integration in Java applications.
Strong knowledge of REST APIs and event-driven architecture.
Familiarity with frontend frameworks and responsive design.
Experience with observability tools (Logback, Prometheus, OpenTelemetry).
Proficiency in CI/CD, Docker, Kubernetes, and version control systems.
Solid understanding of software design principles and architecture.
Preferred Qualifications
Experience with Spring Cloud and microservices components.
Familiarity with vector databases (Pinecone, Milvus, Redis vector).
Knowledge of domain-driven design, CQRS, and reactive programming (Spring WebFlux).
Understanding of OAuth, JWT, and enterprise security protocols.
Exposure to cloud-native AI deployments (AWS Lambda, Azure AI, Google Vertex AI).
Experience with legacy system modernization and hybrid deployments.
Knowledge of AI orchestration, prompt chaining, and multi-agent workflows.
Experience with feature toggles, A/B testing, and canary deployments.
Develop and maintain backend services using Core Java and Spring Boot.
Integrate AI/LLM workflows into Java applications using frameworks like Spring AI.
Design and consume RESTful APIs; familiarity with SOAP/WSDL/XML is a plus.
Build and support event-driven systems using Kafka, JMS, and other messaging platforms.
Collaborate on frontend development using frameworks such as React, Angular, or Vue.
Implement observability tools for logging, metrics, and tracing.
Contribute to CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes).
Apply clean architecture principles and design patterns in system design.
Participate in technical discussions, mentor team members, and collaborate across teams.
Skill Metrics
Restful APIs
Docker
Kubernetes
Ai/LLM
Java
Spring Boot
Required Skills
7–10 years of experience in Java development and Spring ecosystem.
Experience with AI/LLM integration in Java applications.
Strong knowledge of REST APIs and event-driven architecture.
Familiarity with frontend frameworks and responsive design.
Experience with observability tools (Logback, Prometheus, OpenTelemetry).
Proficiency in CI/CD, Docker, Kubernetes, and version control systems.
Solid understanding of software design principles and architecture.
Preferred Qualifications
Experience with Spring Cloud and microservices components.
Familiarity with vector databases (Pinecone, Milvus, Redis vector).
Knowledge of domain-driven design, CQRS, and reactive programming (Spring WebFlux).
Understanding of OAuth, JWT, and enterprise security protocols.
Exposure to cloud-native AI deployments (AWS Lambda, Azure AI, Google Vertex AI).
Experience with legacy system modernization and hybrid deployments.
Knowledge of AI orchestration, prompt chaining, and multi-agent workflows.
Experience with feature toggles, A/B testing, and canary deployments.