Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Full-Stack Feature Delivery: Design, build, and deploy high-performance web applications using React for the front end and Java for the back end.
API & Microservices Architecture: Design, build, and maintain secure, scalable RESTful or GraphQL APIs and microservices in Java
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience in system design, application development, testing, and operational stability
Front-End Mastery: Extensive experience with React.js, TypeScript/JavaScript, HTML5, CSS3, and modern frontend build tools.
Back-End Expertise: Robust background in Java, including framework proficiency with Spring Boot, Spring Security, and Hibernate
AI & Engineering Acumen: Proven experience connecting applications to AI APIs, prompt engineering, fine-tuning, or working with orchestration frameworks
- Data Systems: Experience designing schemas for both traditional relational SQL/NoSQL databases and vector search indexing.
- Soft Skills & Collaboration: Agile/Scrum/Kanban team experience, Git version control expertise, and a passion for staying on the cutting edge of AI advancements
- Understanding of application resiliency. Proficiency in automation and continuous delivery methods.
- Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
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.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred qualifications, capabilities, and skills
Familiarity with modern front-end technologies
Exposure to Python