AI Lead Software Engineer - Java
On-siteJersey City, New Jersey, United States
Job Summary
Lead the design, development, and delivery of high-quality software solutions using Java, Scala, and Spring Boot to solve complex business problems. Drive architectural decisions for scalable, resilient distributed systems and build secure, production-grade services with rigorous code quality standards. Mentor engineers through technical guidance and pair programming to raise team capability while implementing CI/CD automation and reliability patterns. Develop data-intensive workflows and AI-enabled applications, including retrieval-augmented generation and agentic workflows, establishing validation standards and enterprise-authorized AI-assisted engineering practices.
Required Qualifications
- Formal training or certification on software engineering concepts
- 5+ years applied experience
- Demonstrated hands-on experience designing and delivering scalable, secure, resilient distributed systems in a production environment
- Proficiency in Java
- Proficiency in Spring Boot
- Working knowledge of SQL
- Working knowledge of modern user interface frameworks (for example, React)
- Strong understanding of modern architecture patterns, including microservices, event-driven design, and application programming interface-first approaches
- Experience building and operating solutions on public cloud platforms (for example, Amazon Web Services)
- Experience with containerization and orchestration (Docker and Kubernetes)
- Experience implementing continuous integration and continuous delivery pipelines
- Experience with Infrastructure as Code practices
- Practical experience with application programming interface design and integration patterns (for example, REST and GraphQL)
- Practical experience with API security and performance considerations
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting)
- Ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows
- Experience with data sensitivity considerations
- Experience with secure handling of inputs/outputs
- Experience with adherence to resiliency and security expectations
- Experience coaching engineers on safe, compliant adoption within delivery practices
Desired Qualifications
- Advanced expertise in object-oriented design
- Advanced expertise in system design
- Advanced expertise in performance optimization for large-scale services
- Experience with modern data and search technologies (for example, Elasticsearch)
- Experience with databases (for example, Oracle or MongoDB)
- Experience building generative AI solutions, including retrieval-augmented generation architecture
- Experience with orchestration frameworks (for example, LangChain or LlamaIndex)
- Experience with evaluation practices
- Experience creating reusable agent skills, libraries, or patterns that accelerate delivery across engineering teams
- Experience working across hybrid technology ecosystems using cloud services, Databricks, and Kubernetes-based platforms
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