Job Information
Raymond James Financial, Inc. Senior Engineer, Java Full Stack in Saint Petersburg, Florida
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.