Founding Engineer
Other Engineering, IT, Data Science · Full-time
Remote
Shortlyst is hiring its first full-time engineer: a hands-on, product-minded builder who owns the platform end to end and grows the technical team from there.
About Shortlyst
Shortlyst is a B2B PropTech platform that connects commercial retail owner operators and their leasing teams with vetted, activation-ready brands for short-term retail activations: pop-ups, residencies, and short-term leases. We take the sourcing and qualification work off the leasing team's plate and give emerging brands a direct path into great retail space.
About the Role
Marketplace engagement. Own the brand and owner operator experience from sign-up to a signed activation: onboarding, lifecycle email and nudges, on-platform messaging, and the tools that replace current manual processes in the industry. Instrument the funnel and run tests so we know what works.
Product discovery. Join customer and research calls with the founders. Ask why people work the way they do, define what we build next, and rank it against what customers need most.
Matching and machine learning. You will own it and the machine learning system behind matchmaking algorithm: the feedback loops, training data, model evaluation, and retraining pipelines that let it improve with every activation. Use what we learn about which matches converted, for which properties, and under which criteria to make the algorithm measurably smarter over time, and know when a learned model earns its place over a simple rule.
Data foundation. Own our data architecture as we scale, including the pipelines that capture the outcome data our learning systems depend on. Decide when and how to evolve our tooling so data flows cleanly between intake, our platform, and our customers.
Platform and infrastructure. Own APIs, deployments, and reliability, including the infrastructure to train, deploy, and monitor models in production. Make pragmatic calls about what to build properly now and what to come back to later, and explain those tradeoffs to the founders.
Building the team. Tell us what you can do yourself and where we need help, whether that is design, UX, front end, or data science. Bring in contractors when it makes sense, and hire and lead the engineers who come after you.
Must haves
Seasoned builder. 6+ years shipping production software, including time as a founding or early engineer at a startup, or a product you built and launched yourself.
Applied AI and machine learning. Hands-on experience building and shipping machine learning in production, ideally on matching, ranking, or recommendation systems. You have taken a model from data to deployment, and you can design systems that learn continuously from user behavior and outcomes, including feedback loops, evaluation, retraining, and monitoring for drift.
Full stack, strongest on the backend. Deep experience with APIs, relational databases, data modeling, and cloud infrastructure and DevOps (AWS or similar). Productive on the front end using modern frameworks and AI-assisted tooling.
Product judgment. You have decided what to build, not only built what you were handed. You are comfortable on customer calls and can turn what you hear into a ranked plan.
Marketplace and engagement experience. You have worked on a product with marketplace dynamics or a product where onboarding, lifecycle messaging, and retention were the hard problems.
Quantitative fluency. Strong grounding in statistics and data. You can reason about scoring, ranking, and weighting, design experiments, and you know when a model is worth building and when a simple rule will do.
High ownership. When you see something broken, you fix it. You do not wait for permission or a ticket.
Clear communicator. You can explain technical tradeoffs to non-technical founders and customers, and people trust what you tell them.
Here for the long run. You want to join early, earn meaningful equity, and grow into leading the technical side of the company.