Senior Java + AI Engineer

About the Role

We are looking for a highly skilled Enterprise AI Engineer with strong expertise in Java backend development and practical exposure to AI/ML and Generative AI integrations. The ideal candidate will help modernize enterprise platforms by embedding AI capabilities into scalable microservices-based architectures.

This role focuses on integrating AI models into production systems, building enterprise-grade APIs, enabling AI-driven workflows, and collaborating closely with Data Science and Platform Engineering teams.

Key Responsibilities

• Design, develop, and maintain enterprise-grade Java applications using Spring Boot and Microservices architecture.
• Integrate AI/ML and Generative AI capabilities into existing enterprise platforms and workflows.
• Consume and integrate AI models and LLM services through REST APIs, Python services, and cloud AI platforms.
• Collaborate with Data Scientists and ML Engineers to deploy and operationalize AI models in production.
• Build and optimize backend services and data pipelines supporting AI workloads.
• Develop scalable APIs and event-driven services for AI-enabled applications.
• Ensure security, reliability, scalability, and production readiness of AI-integrated systems.
• Work with DevOps and Cloud teams to support CI/CD pipelines and cloud-native deployments.
• Monitor application performance and optimize system efficiency for AI-driven workloads.
• Participate in architecture discussions and contribute to enterprise AI adoption strategies.

Required Skills

• 5+ years of strong hands-on Java development experience.
• Strong expertise in Spring Boot, REST APIs, and Microservices architecture.
• Experience with backend engineering and enterprise application development.
• Exposure to AI/ML/Generative AI integrations in enterprise systems.
• Experience integrating AI services through APIs and Python-based services.
• Strong understanding of cloud platforms such as AWS, Google Cloud Platform, or Azure.
• Familiarity with CI/CD pipelines, DevOps practices, and containerized deployments.
• Strong problem-solving and debugging skills.

Preferred / Nice-to-Have Skills

• Experience working with LLM APIs such as OpenAI, Amazon Bedrock, Azure OpenAI, or Gemini.
• Familiarity with event-driven architectures using Kafka, RabbitMQ, or Pub/Sub.
• Understanding of data engineering fundamentals and ETL/data pipelines.
• Exposure to vector databases, embeddings, or RAG-based architectures.
• Experience with Docker, Kubernetes, and cloud-native deployments.
• Knowledge of AI observability, monitoring, and governance practices.

Qualifications

• Bachelor s or Master s degree in Computer Science, Engineering, or related field.
• Strong communication and collaboration skills.
• Experience working in enterprise-scale distributed systems environments.