Senior Java Developer AI-Enabled

Role Overview

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.

Key Responsibilities

• 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.

Required Technical Skills

• 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.