Java AI Lead Software Engineer
$150,000–$200,000 year
On-siteColumbus, Ohio, United States
Job Summary
Own end-to-end delivery of complex backend components, embedding AI-native capabilities like agentic workflows and LLM-powered features into core product experiences. Execute software solutions, design, development, and technical troubleshooting to build innovative approaches that break down technical problems. Create secure, high-quality production code and maintain algorithms running synchronously with appropriate systems. Drive team adoption of enterprise-authorized AI-assisted engineering practices, including code review, refactoring, and test strategy acceleration, while establishing consistent validation standards. Participate actively in design reviews and architecture discussions to identify performance bottlenecks and propose optimizations. Mentor junior engineers through code reviews and technical guidance while maintaining clear communication with peers and stakeholders. Requires 7+ years of applied experience in Java, distributed systems, and cloud platforms like AWS, with proficiency in Spring Boot, Kafka, and microservices.
Required Qualifications
- Formal training or certification on software engineering concepts
- 7+ years applied experience
- Experience in designing and developing distributed systems using Java
- Strong knowledge in Core Java (Java 21+)
- Strong knowledge in Spring Boot
- Strong knowledge in React
- Strong knowledge in REST
- Strong knowledge in Kafka
- Strong knowledge in Microservices
- Strong knowledge in Agile
- Strong knowledge in DevOps
- Hands-on practical experience using AI coding assistants (GitHub Copilot, Cursor, Claude, etc.)
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
- Experience in object oriented analysis and design (OOAD)
- Proficiency in automation and continuous delivery methods
- Proficiency in all aspects of the Software Development Life Cycle
- Experience working with cloud platforms such as AWS
- Experience on asynchronous communication using messaging/streaming systems (Kafka, RabbitMQ, or equivalents)
- Ability to design and optimize data models either in relational or NoSQL databases
- Ability to handle data consistency, replication, sharing, and transactional boundaries
- Familiarity with containerization and orchestration tools: Docker, Kubernetes
- Knowledge on integration with CI/CD pipelines for automated build, test, and deployment
- Exposure to cloud technologies
Desired Qualifications
- Advanced knowledge of application, data, and infrastructure architecture disciplines
- Strong written and oral communication and excellent presentation and influencing skills
- Familiarity with modern front-end technologies
- Practical cloud native experience
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