Founding Engineer – Full-Stack Generalist (Remote, Full-Time) [AS324]

About Smart Working

At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being.

Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.

Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.

About the Role

As a Founding Engineer, you will become the first and only in-house engineering headcount for an AI-native Professional Services Automation platform serving growing agencies and consultancies. The live platform brings projects, people, time and financials into one operating view, with ambient AI monitoring delivery and recommending action.

You will have end-to-end ownership across frontend, backend and infrastructure. You will harden, scale and evolve the existing platform while continuing to deliver customer-facing improvements. The role is a senior/staff-level individual contributor position rather than a CTO role today, although its scope may grow with the company.

• Own the product end-to-end as a solo generalist, building, shipping and deploying across frontend, backend and infrastructure without a supporting team.
• Keep the live platform healthy, including handling incidents and defects and managing safe releases and rollback.
• Use AI/agentic coding tools to increase personal output while independently verifying correctness, security and robustness rather than trusting AI-generated output blindly.
• Lead the platform towards ISO 27001 and SOC 2 readiness by April 2027, translating external compliance requirements into concrete engineering controls; prior certification experience is not required.
• Make the AI assistant and orchestration features reliable, measurable and safe.
• Decide what to preserve, isolate, improve or replace in the current platform based on customer risk and commercial value, without undertaking an unnecessary rebuild.
• Move fluidly across frontend and backend as a true full-stack generalist, with no fixed frontend/backend split.
• Harden, scale and evolve the existing product, including delivery intelligence, AI assistant, SOW ingestion, project/resource/commercial management and a beta orchestration layer, while continuing to ship customer-facing improvements.
• Work solo end-to-end as the company's hands-on technical owner, with the potential to help decide on and shape the first supporting engineering hire once funding closes.
• Work effectively with high ambiguity, evolving scope and close, direct collaboration with both technical and non-technical founders.

5+ years of professional software engineering experience, ideally including early-stage startup or high-ownership experience.

5+ years of senior-level full-stack engineering experience across a React/TypeScript frontend and Node/Postgres-style backend, or a strong modern JavaScript/TypeScript full-stack equivalent such as Next.js or Vue/Nuxt, with proven end-to-end ownership.

4+ years of senior-level experience with solo ownership of cloud deployment, releases and CI/CD, or a proven record of shipping and operating production infrastructure without a dedicated DevOps/platform team.

3+ years of senior-level experience with Postgres/Supabase or equivalent, including row-level security and edge functions. Deep relational database experience with another Postgres-based backend, Firebase or PlanetScale is also acceptable.

1–2+ years of senior-level experience using AI-assisted/agentic coding tools such as Cursor, Claude Code or Copilot to ship production software, or demonstrable heavy and disciplined use of LLMs within a professional development workflow.

Have a clear method for checking AI-generated output rather than trusting it blindly.

Be comfortable operating as a senior/staff-level individual contributor generalist and owning a product or platform end-to-end solo or near-solo; formal project-leadership titles are not required.