We are a small, high-output team building across a complex technical surface: consumer marketplace, provider-facing scheduling tools, interoperability infrastructure, revenue cycle tooling, and AI-augmented workflows. We scale our impact through AI-native development practices, tight feedback loops, and engineers who own outcomes rather than tickets.
As Senior Engineering Manager, you will lead a cross-functional engineering team and partner with the product organization to deliver on our ambitious roadmap. We expect roughly 20% of your time to be spent writing code, reviewing architecture, or directly shaping technical decisions. The majority of your time will be spent establishing engineering processes, managing technical breakdown of features, reporting progress to leadership, career development of your reports, and exploring new technologies/vendors.
You will report to our CPO and partner closely with Product, Operations, and Data to ship the systems that run our business. You are expected to be genuinely AI-native: not just comfortable with AI tooling, but actively shaping how your team uses it. That means deploying agents, building evaluation frameworks, and coaching engineers to work at a level of throughput that wasn't possible two years ago.
As a scale-up business, you can expect your role to develop over time. Here are some of the types of things you could be getting involved in:
- Lead and develop a team of engineers across multiple product domains, owning velocity, process, performance, technical growth, and team culture
- Remain a consistent technical contributor by writing production code, leading design reviews, and pairing with engineers on complex problems.
- Define and enforce engineering standards across code quality, system design, testing discipline, deployment practices, and incident response
- Drive the team's AI-native operating model by identifying where AI agents can replace or accelerate engineering workflows, building evaluation frameworks to measure output quality, and coaching engineers to leverage AI tooling as a primary development instrument rather than an occasional aid
- Partner with Product to refine roadmaps, push back on scope where necessary, and ensure the team is working on the highest-leverage problems at any given time
- Own the architecture of your team's systems by making build vs. buy decisions, managing technical debt deliberately, and ensuring the stack can support the growth trajectory of the business
- Contribute to Scan.com http://Scan.com's broader engineering culture through interview loops, cross-team design reviews, engineering all-hands, and institutional knowledge.