Job Description Enterprise AI Engineer (Java + AI)
Role: Senior Java + AI Engineer
Experience: 5 10 Years
Location: Austin, TX / Sunnyvale, CA
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.
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