Senior Full Stack Software Engineer

The opportunity

Evolve the architecture of Navierre's platform and keep it reliable, maintainable, secure and fast. This is a hands-on role across the whole stack, with ownership of technical decisions from design through production. We care about fundamentals: sound system design, separation of concerns, modularity, abstraction, testability and disciplined practice. We expect engineers to weigh architectural trade-offs, challenge unnecessary complexity and make decisions that keep the system maintainable in the long term. The stack includes Java, Spring Boot, AWS, PostgreSQL, React, Next.js, TypeScript and React Native. We use AI-assisted development tools and expect a practical grasp of context management, token use and the responsible use of AI in engineering.

What you'll do

• Shape the architecture. Design, review and evolve systems with clear component boundaries, well-defined interfaces, the right abstractions and minimal coupling.
• Apply engineering principles. Use separation of concerns, design patterns and established software engineering practice consistently.
• Modernize the codebase. Refactor existing systems, reduce technical debt, remove unnecessary complexity and improve structure, readability and maintainability.
• Build the backend. Design and develop Java and Spring Boot services, REST APIs, integrations and distributed systems.
• Run the cloud. Architect, deploy, secure, troubleshoot and optimize AWS infrastructure and cloud-native applications.
• Own the data layer. Design and optimize PostgreSQL databases: data modeling, indexing, query performance, transactions and data integrity.
• Build the front end and the mobile apps. Develop and maintain applications in React, Next.js, TypeScript and React Native to consistent architectural and coding standards.
• Make quality automatic. Establish unit, integration and end-to-end testing, and design code to be testable.
• Keep it fast and reliable. Diagnose and resolve performance bottlenecks, production defects, scaling and reliability issues.
• Improve delivery. Strengthen CI/CD pipelines, infrastructure as code, automated quality gates, monitoring and deployment processes.
• Use AI well. Bring AI coding tools into the workflow with effective context engineering, token discipline and rigorous validation of generated code.
• Own it end to end. Take responsibility for technical decisions and solutions through their whole lifecycle, from design to production operations.

What you bring

• Significant experience designing, developing and operating complex production software, and the ability to weigh technical trade-offs independently and own complex engineering problems.
• Advanced Java and Spring Boot, object-oriented programming and distributed systems, with a strong command of design principles, architectural patterns, concurrency and API design.
• Deep hands-on AWS experience across architecture, networking, security, deployment and operations.
• Strong PostgreSQL: relational data modeling, SQL optimization and database performance.
• Production experience with React, Next.js, TypeScript and React Native.
• A record of improving existing codebases and paying down technical debt, backed by automated testing, CI/CD, observability and production troubleshooting.
• Practical use of AI coding assistants: context management, model selection and token-efficient workflows.

Also valued

• Healthcare or insurance data, including privacy, consent and security requirements.
• Event-driven or batch data pipelines and large relational datasets.
• A history of mentoring engineers and raising a team's standards.

Your first 90 days

1. First 30 daysLearn the platform and its history, ship small changes through the full pipeline and write down what you would change.
2. By 60 daysLead one architectural improvement or refactor end to end, with tests and monitoring in place.
3. By 90 daysOwn a core service or surface, with the practices and quality gates you set in use by the team.

How success is measured

Reliability and performance in production, the pace and safety of delivery, the debt retired, and the quality of the architectural decisions others build on.

How you work with the team

Engineering leadership owns the roadmap. Partner with Applied AI on the intelligence the platform runs, with Solutions & Delivery on what customers need, and with product on what comes next.

What to send

Include a resume and examples of production systems you have designed or improved, with your contribution clearly stated. Be prepared to discuss an architecture you changed, a performance problem you solved and how you use AI tools in your own work.