**This position follows our hybrid workstyle policy: Expected to be in a Raymond James office location a minimum of 10-12 days a month.** **_Please note: This role is not eligible for Work Visa sponsorship, either currently or in the future._** **Responsibilities** + Design, develop, test, deploy, and support scalable, high-performance full stack applications using Java, Spring Boot, REST services, Angular, and relational databases. + Analyze system requirements and identify program interactions, data flows, and appropriate interfaces between impacted components and subsystems. + Participate actively in architecture, design, and code reviews to ensure scalable, secure, and maintainable solutions. + Lead development efforts for iterative project deliverables across the software development lifecycle (SDLC), including planning, coding, testing, deployment, and operational support. + Guide engineers by promoting technical excellence, curiosity, and sound engineering principles. + Collaborate with cross-functional partners (Product, Design, QA, DevOps, Project Management) to translate business requirements into high-quality technical solutions. + Build strong relationships with Development Managers, Engineers, and Project Managers across teams to drive alignment and delivery. + Champion Agile methodologies and contribute technical leadership in sprint planning, backlog refinement, and release execution. + Continuously raise the bar on engineering excellence through adherence to coding standards, testing discipline, CI/CD best practices, and operational readiness. + Stay current with emerging technologies, frameworks, and tools; develop proof-of concepts to evaluate and drive innovation where appropriate. **AI-Enabled Engineering Practices** + Apply AI pair-programming tools (e.g., GitHub Copilot / Copilot Chat) to accelerate development, refactoring, documentation, and test creation—while maintaining full ownership and accountability for code quality. + Use structured prompt engineering techniques (clear task framing, constraints, examples, iterative refinement) to generate accurate, secure, and maintainable code suggestions. + Integrate AI into the inner development loop (IDE) for unit and integration test generation and rapid validation of functionality. + Leverage AI tools to review diffs, suggest improvements, and surface potential defects early; ensure all AI-generated output is validated through testing and peer review. + Partner with product and design teams to translate user stories into high-quality prompts and working code; maintain reusable prompt libraries and playbooks. + Utilize AI to automate repetitive engineering tasks (scaffolding, boilerplate, data transformation) to focus on complex problem-solving and architectural design. + Perform other duties and responsibilities as assigned. **Core Technical Skills** + Strong experience in Java and J2EE development. + Proficiency in building RESTful services using Spring Boot. + Experience with ORM frameworks (Hibernate preferred). + Hands-on expertise writing advanced PL/SQL, stored procedures, and performance-optimized queries. + Experience with Angular (Angular 12+ preferred), JavaScript, HTML5, CSS3, responsive design, and reactive programming concepts is a plus. + Solid understanding of system design, API design, data modeling, and application performance tuning. + Strong debugging, problem-solving, and analytical skills. **AI-Augmented Development Expertise** + Hands-on experience using GitHub Copilot (or equivalent AI coding assistants) within modern IDEs (VS Code, JetBrains, Windsurf), including chat-based workflows and inline completions. + Demonstrated prompt engineering capability: crafting, iterating, and evaluating prompts; decomposing work into AI-friendly steps; applying guardrails and constraints to ensure secure and maintainable outputs. + Ability to critically evaluate AI-generated code for correctness, security, performance, scalability, and readability, supported by disciplined debugging and strong test practices. + Working knowledge of secure AI usage in enterprise environments, including protection of secrets/PII, adherence to data boundaries, and compliance with organizational policies. + Experience leveraging AI to support test-driven development (TDD), including generating tests, validating behavior, and enforcing coverage and quality thresholds.