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Flipdish is a SaaS platform helping independent restaurant and takeaway owners run their businesses with integrated tools spanning online ordering, marketing, loyalty, point of sale, menu optimization, and operational automation. The company is AI-first and venture-backed.
As a Commercial Systems Engineer, you will build the products, systems, automations, and internal tools that enable Flipdish's commercial teams—Sales, Onboarding, Partnerships, Marketing, and Operations—to scale efficiently. You'll work on high-impact initiatives across AI Marketing, Google Business Profile (GBP), Growth Operations, and wider commercial workflows.
You will own the full lifecycle: discovery and scoping through build, deployment, monitoring, iteration, and decommissioning of systems no longer delivering value. Key responsibilities include:
- Design, build, deploy, and maintain systems supporting commercial products and Growth Operations initiatives.
- Build internal tools and automation enabling Sales, Onboarding, Partnerships, and Marketing to scale without proportional headcount growth.
- Deliver product improvements and monitoring for Google Business Profile initiatives, improving discovery, routing accuracy, ordering coverage, and order-fee revenue.
- Build scalable automation for AI Marketing, including campaign setup, quality assurance, monitoring, reporting, alerting, and revenue attribution.
- Leverage AI-assisted engineering tools (Claude Code, Cursor, Vercel, LLM APIs) to ship faster and unlock capabilities otherwise difficult or costly to deliver.
- Own the path from local development to production on AWS, including deployment, observability, incident response, and service reliability.
- Build dashboards and instrumentation to track adoption, operational performance, and commercial outcomes.
- Take end-to-end ownership: scope opportunities, ship effective solutions, measure impact, iterate based on evidence, and decommission underperforming work.
- Challenge poor decisions and propose better ways of working.
Within six months, success means shipping reliable, production-ready tools across AI Marketing, GBP, or commercial operations; reducing manual effort in high-volume workflows; establishing clear adoption and revenue-attribution metrics; improving commercial outcomes (order-fee revenue, campaign time-to-launch, conversion, sales-cycle speed); and earning trust across Sales, Onboarding, Partnerships, Marketing, Product, and Operations.
Requirements:
- 4+ years of software engineering experience, ideally building production applications with the MERN stack (MongoDB, Express, React, Node.js).
- Shipped and deployed real products on AWS; comfortable owning the path from local development to production, including troubleshooting.
- Fluent in AI-assisted engineering; regularly use 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 than project count.
- Connect engineering work to commercial outcomes; explain in plain language why a feature or system mattered to the business.
- Communicate clearly with non-engineers; translate between needs of Sales, Commercial, Partnerships, Marketing, and Engineering without losing either perspective.
- Use data and instrumentation to understand adoption, diagnose problems, prioritize work, and evaluate whether solutions deliver value.
- Take high ownership; do not wait to be told what to do; follow problems through to resolution.
- Challenge poor decisions and propose better ways of working.
Desirable experience:
- Working with martech or adtech APIs, particularly Google Business Profile, Google Ads, or Meta.
- Building AI agents, retrieval-augmented generation (RAG) systems, or AI-native workflows.
- Serverless or edge deployments (AWS Lambda, Vercel Functions, Cloudflare Workers).
