Java Developer AI-Enabled

V-Work Infotech Solutions INC

United States

2 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Software Applications Microsoft Azure Cloud Computing Code Review Continuous Integration Relational Databases Software Design Patterns DevOps

+45 more

Distributed Systems Amazon DynamoDB Java Platform Enterprise Edition (J2EE) Github Java Virtual Machine (JVM) Spring Framework Python (Programming Language) PostgreSQL Enterprise Messaging Systems MongoDB NoSQL Oracle (Applications) Performance Tuning RabbitMQ Redis Prometheus Search Technologies Software Engineering SQL Databases Web Services Multithreading Google Cloud Java Application Server Enterprise Software Applications Spring Cloud Retrieval-Augmented Generation Large Language Models Grafana Concurrency Prompt Engineering Spring-boot Generative AI Gitlab Git Event Driven Architecture Infrastructure Automation Frameworks Apache Kafka Machine Learning Operations Restful APIs Terraform Splunk Api Management Docker Jenkins Microservices

Job description

Design, develop, and maintain scalable Java/Spring Boot microservices and RESTful APIs.
Build high-performance, distributed, cloud-native applications using Java 11/17/21.
Develop and integrate AI/GenAI capabilities into existing enterprise applications.
Work with LLMs, prompt engineering, RAG, embeddings, vector databases, and AI APIs.
Design AI-powered services using frameworks such as LangChain4j, Spring AI, or equivalent Java AI frameworks.
Integrate LLM providers such as Azure OpenAI, OpenAI, AWS Bedrock, or Google Vertex AI.
Build secure APIs and services for AI-powered applications.
Develop event-driven architectures using Kafka, RabbitMQ, or similar messaging platforms.
Work with relational and NoSQL databases including PostgreSQL, Oracle, MongoDB, DynamoDB, or Redis.
Implement automated unit, integration, and API testing.
Participate in architecture discussions, technical design, code reviews, and performance optimization.
Deploy and operate applications in AWS/Azure/Google Cloud Platform environments.
Implement CI/CD pipelines using Jenkins, GitHub Actions, GitLab, or Azure DevOps.
Collaborate with product managers, architects, data engineers, DevOps engineers, and AI/ML teams.

Requirements

We are seeking a Senior Java Developer (AI-Enabled) with 10+ years of experience in enterprise Java development, distributed systems, microservices, and cloud-native applications. The ideal candidate will combine strong Java engineering expertise with hands-on experience integrating Generative AI, LLMs, RAG, and AI-enabled capabilities into enterprise applications., * 10+ years of software development experience.

Strong expertise in Java, J2EE, Spring, Spring Boot, Spring Cloud.
Strong experience with REST APIs, microservices, distributed systems, and API integration.
Java 11/17/21 experience.
Strong knowledge of multithreading, concurrency, JVM, design patterns, and performance tuning.
Experience with SQL and relational databases.
Experience with Kafka/event-driven architecture.
Hands-on cloud experience with AWS, Azure, or Google Cloud Platform.
Strong Git and CI/CD experience.

AI / GenAI Requirements

Hands-on experience integrating Generative AI/LLM capabilities into applications.
Experience with RAG (Retrieval-Augmented Generation) architectures.
Knowledge of embeddings, vector search, semantic search, and vector databases.
Experience with LangChain4j, Spring AI, or similar frameworks.
Experience working with Azure OpenAI, OpenAI, AWS Bedrock, or Vertex AI.
Understanding of prompt engineering, function/tool calling, AI agents, and structured LLM outputs.
Knowledge of AI application security, including prompt injection, data privacy, access control, and responsible AI practices.

Preferred Skills

Python exposure for AI/ML integration.
Experience with Pinecone, OpenSearch, pgvector, Weaviate, Qdrant, or Redis Vector Search.
Docker and Kubernetes.
Terraform or other Infrastructure as Code tools.
Observability using Splunk, ELK, Prometheus, Grafana, or OpenTelemetry.
Experience modernizing legacy Java applications into cloud-native microservices.
Experience working in Agile/Scrum environments.