EFS Resource Pool F2C 170934

ava & AI Developer Job Description Experience: 39 Years | Full-Time Responsibilities Design and develop scalable Spring Boot microservices and REST APIs with OAuth2 security Build server-side web interfaces using Thymeleaf and integrate with backend services Work with Oracle/MongoDB databases and implement Hibernate-based data access layers Build and integrate Generative AI / RAG pipelines using LangChain, LangGraph, CrewAI, or AutoGen Develop AI Agents and Multi-Agent Systems with LLM integrations and Vector Databases Implement MLOps practices and AI Guardrails to ensure responsible, safe, and governed AI deployments Use Amazon Q and GitHub Copilot to accelerate development and AI-assisted engineering Collaborate with scrum teams and product owners to deliver high-quality, high-performance SaaS solutions Skills Required Java/J2EE, Spring, Spring Boot, Microservices, Multi-Threading, Hibernate, Thymeleaf REST APIs, Web Services, OAuth2, Tomcat/WebLogic, Oracle, MongoDB, BIRT Reports Python, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel LLMs, Prompt Engineering, RAG, Conversational AI, Vector DBs (Pinecone, FAISS, OpenSearch) MLOps model versioning, monitoring, deployment pipelines, and drift detection AI Guardrails content filtering, safety policies, responsible AI, and prompt injection prevention AWS (Lambda, S3, API Gateway, DynamoDB, ECS/EKS) | Docker, Git, CI/CD Hands-on experience with Amazon Q Developer and GitHub Copilot for AI-assisted coding AWS Certifications and Angular experience are a plus ##LI-DNIava & AI Developer Job Description Experience: 39 Years | Full-Time Responsibilities Design and develop scalable Spring Boot microservices and REST APIs with OAuth2 security Build server-side web interfaces using Thymeleaf and integrate with backend services Work with Oracle/MongoDB databases and implement Hibernate-based data access layers Build and integrate Generative AI / RAG pipelines using LangChain, LangGraph, CrewAI, or AutoGen Develop AI Agents and Multi-Agent Systems with LLM integrations and Vector Databases Implement MLOps practices and AI Guardrails to ensure responsible, safe, and governed AI deployments Use Amazon Q and GitHub Copilot to accelerate development and AI-assisted engineering Collaborate with scrum teams and product owners to deliver high-quality, high-performance SaaS solutions Skills Required Java/J2EE, Spring, Spring Boot, Microservices, Multi-Threading, Hibernate, Thymeleaf REST APIs, Web Services, OAuth2, Tomcat/WebLogic, Oracle, MongoDB, BIRT Reports Python, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel LLMs, Prompt Engineering, RAG, Conversational AI, Vector DBs (Pinecone, FAISS, OpenSearch) MLOps model versioning, monitoring, deployment pipelines, and drift detection AI Guardrails content filtering, safety policies, responsible AI, and prompt injection prevention AWS (Lambda, S3, API Gateway, DynamoDB, ECS/EKS) | Docker, Git, CI/CD Hands-on experience with Amazon Q Developer and GitHub Copilot for AI-assisted coding AWS Certifications and Angular experience are a plus