Full Stack Software Engineer

Red Oak

6d•Hybrid

About The Position

A Full Stack Software Engineer will play a key role in the ongoing evolution of the core Red Oak platform. This is a complex, multi-tenant system with deep business logic, Compliance-Grade AI solutions, legacy components, and rapidly expanding modern services. This role offers the opportunity to make a significant impact by delivering innovative products and features to our ever-expanding client base. As a Full-Stack Software Engineer at Red Oak you'll be immersed in every phase of the software development life cycle, from brainstorming in design meetings to fine-tuning and debugging based on client feedback. Your role will involve designing, developing, testing, and supporting your features, ensuring they not only meet client needs but also live up to our high standards of quality. In addition, you will help to establish team norms around responsible, high-leverage AI-assisted development. Starting out, your primary focus will be contributing to a ground-up redesign of our enterprise SaaS platform's user interface and user experience. You'll be involved from day one, helping shape component architecture and setting the standard for how our product looks and feels for years to come. Strong UI instincts and a high bar for quality are a must.

Requirements

3–5 years of experience in software development.
Proficiency in Vue, Angular, or React (Vue 3 preferred).
Strong knowledge of JavaScript, HTML, and CSS3.
Experience with Java EE.
Understanding of database technologies (SQL, NoSQL).
Ability to leverage agentic AI tools (e.g. Claude, Cursor, Copilot) as a core part of your development workflow, with a bias toward shipping faster and smarter.

Nice To Haves

Familiarity with Java MVC frameworks.
Familiarity with microservice and micro-frontend architectures.
Proficiency with Microprofile REST Client.
Proficiency in writing tests using Vitest, Jest, and JUnit.
Familiarity with TypeScript.
Experience with Bootstrap 4 or Bootstrap 5.
Experience creating reusable components using Vue 3.
Prior experience in a SaaS software company and/or product development environment.
Understanding of web accessibility standards (WCAG).
Experience with Agile methodologies and tools such as Jira.
Familiarity with continuous integration/continuous deployment (CI/CD) processes.
Ability to adapt to new feature requirements or direction based on client or internal feedback.

Responsibilities

Translate complex UX designs into pixel-precise, accessible, and performant frontend implementations, including component architecture decisions, state management patterns, and responsive layout systems.
Build and maintain scalable full-stack applications with a focus on integrating or exploring AI/ML capabilities, including LLMs, RAG pipelines, agentic workflows, and MCP-based tool integrations.
Contribute to backend services within your domain, developing working knowledge of their intent, design, and evolution.
Support improvements to legacy behaviors by applying modern workflow patterns under the guidance of senior engineers.
Support platform reliability by writing high-quality, testable code and collaborating with QA to ensure strong unit, integration, and API coverage across critical workflows.
Participate in code reviews and technical discussions to build consistency and maintainability across the team.
Troubleshoot and resolve complex issues involving multi-step workflows, state transitions, service interactions, and legacy-to-modern integration points.
Contribute to architecture documentation, onboarding materials, and technical design records to support long-term team scalability.
Support compliance initiatives with secure coding, documentation, and process rigor.
Collaborate cross-functionally to design AI-powered features, evaluate emerging models and tools, and own the full lifecycle from prototype to deployment.
Leverage AI coding tools (GitHub Copilot, Cursor, Claude, etc.) to accelerate development velocity, write and review AI-generated code with a critical eye, and champion best practices for safe, effective AI-assisted engineering across the team.