Java AI Engineer

Java AI Engineer

We are seeking a highly skilled Java AI Engineer to design, develop, and deploy AI-powered enterprise applications using Java technologies and modern Generative AI frameworks.

The ideal candidate should possess strong expertise in Java, Spring Boot, Microservices, Cloud Technologies, Large Language Models (LLMs), AI Agents, and Retrieval-Augmented Generation (RAG) architectures.

The role involves building intelligent business solutions, integrating Generative AI services, developing AI agents, and delivering scalable cloud-native applications for enterprise customers.

Key Responsibilities

• Design, develop, and maintain enterprise applications using Java, Spring Boot, and Microservices.
• Build and integrate AI-powered applications using OpenAI, Azure OpenAI, and other LLM platforms.
• Develop AI chatbots, virtual assistants, enterprise copilots, and intelligent search solutions.
• Design and implement RAG (Retrieval-Augmented Generation) solutions using vector databases.
• Develop AI agents and orchestration workflows using LangChain4j, Spring AI, AutoGen, or similar frameworks.
• Create RESTful APIs and backend services for AI applications.
• Implement prompt engineering and model optimization techniques.
• Collaborate with Product Owners, Architects, Data Engineers, and Business stakeholders.
• Deploy and manage AI workloads on cloud platforms.
• Ensure application performance, scalability, security, and compliance.
• Participate in code reviews, architecture discussions, and Agile ceremonies.
• Troubleshoot and optimize AI application performance and operational costs.

Required Technical Skills

Core Java Technologies

• Java 11/17/21
• Spring Boot
• Spring MVC
• Spring Security
• Spring Data JPA
• Hibernate
• RESTful Web Services
• Microservices Architecture
• Maven
• Gradle

AI / Generative AI

• OpenAI APIs
• Azure OpenAI Service
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents
• LangChain4j
• Spring AI
• Semantic Kernel (Optional)
• Vector Databases:
• Pinecone
• ChromaDB
• Weaviate
• Milvus
• AI Model Evaluation and Monitoring

Cloud Technologies

• Microsoft Azure
• AWS
• GCP
• Azure AI Services
• Azure AI Search
• Azure Functions
• Kubernetes (AKS / EKS / GKE)
• API Gateway
• Cloud Storage Services

Database Technologies

• SQL Server
• Oracle
• PostgreSQL
• MySQL
• MongoDB
• Cosmos DB

DevOps & Automation

• Git
• GitHub
• Azure DevOps
• Jenkins
• Docker
• Kubernetes
• SonarQube
• CI/CD Pipelines

Preferred Skills

• Experience building Enterprise AI Copilots.
• Knowledge of Machine Learning and MLOps.
• Experience with Apache Kafka and Event-Driven Architecture.
• Exposure to Databricks and Data Engineering concepts.
• Knowledge of OCR, Speech-to-Text, and Document Intelligence solutions.
• Experience with Power Platform and Copilot Studio integrations.
• BFSI, Capital Markets, Wealth Management, or Banking domain experience.
• Understanding of Responsible AI and AI Governance frameworks.