About the Role
As a Software Engineer, you will implement full-stack solutions, review code, and solve complex engineering problems across multiple client projects and our internal suite of tools. We use AI coding tools heavily in our daily development workflow. You should expect to spend less time typing boilerplate and more time on solutioning decisions, implementation quality, code reviews, debugging, and solving the hard 20% that AI cannot reliably reason about. This includes edge cases, legacy system quirks, unclear requirements, business logic, API integrations, security concerns, and production issues.
You will still write code directly, especially where engineering judgment, context, and precision matter most. You will work closely with project teams, and with clients when needed, to understand problems firsthand, clarify trade-offs, and turn messy real-world requirements into reliable software.
Responsibilities
- Design and build solutions for new projects, ongoing builds, maintenance work, and internal tools.
- Implement full-stack features across frontend, backend, APIs, CMS platforms, integrations, and cloud-hosted applications.
- Use AI coding tools as your default workflow for scaffolding, implementation support, refactoring, debugging, documentation, and test generation.
- Take AI-accelerated work to production-grade quality. AI may get you most of the way there fast, but you own the part that handles edge cases, and business rules.
- Review and audit code produced by both human developers and AI assistants.
- Catch issues in AI-generated code, including logic, APIs, weak error handling, security gaps, missing edge cases, and over-engineered solutions.
- Proactively identify and resolve issues related to business logic, API integrations, performance, accessibility, maintainability, and security.
- Work directly with project teams, and with clients when needed, to diagnose problems firsthand instead of only executing a written spec.
- Support and review the work of other developers, including junior and mid-level team members.
- Build and maintain AI coding workflows for the team, including prompt patterns, tool configurations, reusable instructions, automations, and review checklists.
- Troubleshoot staging and production issues across code, hosting, databases, APIs, logs, and configuration.
- Communicate progress, blockers, risks, and changes clearly on the platforms the team already uses.
Experience Needed
- 4+ years of professional full-stack development experience.
- Strong experience with modern web frameworks such as React, Node.js, and Next.js. Python experience is a plus.
- Degree in Computer Science, Software Engineering, or a related discipline, or equivalent practical experience.
- Experience working with CMS or eCommerce platforms such as WordPress, Drupal, Magento, or similar.
- Experience integrating systems using REST APIs, GraphQL APIs, and web hooks.
- Comfortable with cloud hosting platforms such as AWS, Kinsta, DigitalOcean or similar.
- Experience with team-based version control and standard development workflows: scope, build, review, deploy, support.
- Real, daily production experience with AI coding tools such as Claude Code, Cursor or similar.
- Strong debugging ability across frontend, backend, database, infrastructure, and third-party integrations.
- Solid understanding of technical fundamentals, including DNS, SSL, caching, databases, authentication, authorization, API design, error handling, logging, testing, deployment, and basic security.
- Experience with CI/CD, Linux, environment variables, secrets, staging environments, production environments, logs, backups, and rollbacks is preferred.
- Experience with workflow automation tools such as n8n, Zapier, Make, or similar is a plus.
What Will Help You Succeed
- Good written and spoken communication. You will work with people across countries and time zones.
- Discipline to manage your own time and output without close supervision.
- A strong enough grasp of fundamentals to tell when AI is right, when it is confidently wrong, and when it is just guessing.
- Good habits managing multiple projects and people at once.
- Ability to ask good questions before building the wrong thing.
- Care for the user, client, and business problem behind the technical request.
- Comfort moving between code, logs, documentation, meetings, and production issues.
- Practical judgment on when to build properly, when to simplify, and when to flag risk.
- A habit of leaving code, documentation, workflows, and processes better than you found them.
- Ability to guide other developers while still delivering your own work.
- Strong research habits using documentation, source code, logs, tests, search, and AI tools to understand unfamiliar problems and verify solutions.