Commercial Systems Engineer

Job description

About Flipdish At Flipdish, we’re turning the tables in favour of independent restaurant and takeaway owners by offering them powerful, simple-to-use tech solutions backed by real human support. Everything we do is designed to make running a restaurant satisfyingly simple in a world that’s anything but. About the role You’ll join Flipdish as a Commercial Systems Engineer, building the products, systems, automations, and internal tools that help our commercial teams scale. Your work will support high-impact initiatives across AI Marketing, Google Business Profile (GBP), Growth Operations, and wider commercial workflows. You’ll partner closely with Sales, Onboarding, Partnerships, Marketing, Product, and Operations to turn revenue and efficiency problems into practical, production-ready solutions. This is a hands-on engineering role for someone who moves comfortably from discovery and scoping through build, deployment, monitoring, iteration, and—when something is no longer delivering value—decommissioning. Success in this role looks like faster delivery of commercial initiatives, higher adoption of the tools you build, less manual work, stronger revenue attribution, and measurable improvements in revenue, conversion, and operational efficiency. What you’ll own Design, build, deploy, and maintain systems that support commercial products, Growth Operations initiatives, and internal operations. Build internal tools and automation that enable Sales, Onboarding, Partnerships, and Marketing to scale without linear headcount growth. Deliver product improvements and monitoring for Google Business Profile initiatives, helping improve discovery, routing accuracy, ordering coverage, control, and order-fee revenue. Build scalable automation for AI Marketing, including campaign setup, quality assurance, monitoring, reporting, alerting, and revenue attribution. Use AI-assisted engineering tools—including Claude Code, Cursor, Vercel, and LLM APIs—to ship faster and unlock capabilities that would otherwise be difficult or costly to deliver. Own the path from local development to production on AWS, including deployment, observability, incident response, and ongoing service reliability. Build dashboards and instrumentation with internal partners to track adoption, operational performance, and commercial outcomes. Take end-to-end ownership of problems: scope the opportunity, ship an effective solution, measure its impact, iterate based on evidence, and decommission work that is not earning its keep. Challenge poor decisions and propose better ways of working. Constructive challenge is a responsibility—prioritising harmony over truth or progress is a failure of responsibility. What success looks like Within your first six months, you will have: Shipped reliable, production-ready tools or automations across AI Marketing, GBP, or commercial operations, with clear ownership and monitoring in place. Reduced manual effort and improved speed, quality, or scalability in at least one high-volume commercial workflow. Established clear adoption, revenue-attribution, and operational metrics for the systems you own, allowing teams to make better decisions. Improved commercial outcomes such as order-fee revenue, campaign time-to-launch, conversion, sales-cycle speed, or effort per opportunity. Earned the trust of Sales, Onboarding, Partnerships, Marketing, Product, and Operations by translating business problems into practical technical solutions and following through from concept to measurable impact. About you You’ll thrive in this role if you: Have 4+ years of software engineering experience, ideally building production applications with the MERN stack: MongoDB, Express, React, and Node.js. Have shipped and deployed real products on AWS and are comfortable owning the path from local development to production, including troubleshooting when something breaks. Are fluent in AI-assisted engineering and regularly use tools such as Claude Code, Cursor, Vercel, and LLM APIs to improve delivery speed and capability. Can point to products you have built that real users adopted. Meaningful usage and outcomes matter more to us than the number of projects completed. Connect engineering work to commercial outcomes and can explain, in plain language, why a feature or system mattered to the business.&l