Rula Engineering Team

Our leadership is mission-driven and hands-on, with a clear vision for making quality mental healthcare accessible at scale. Our leaders prioritize building genuine partnerships with the teams they work with, and they combine a healthy, stable business with a fast, iterative execution style. That gives us both the foundation and the speed to tackle ambitious problems, including new investments like AI-assisted therapy.

We structure on-call to protect our personal time. Primary on-call engineers acknowledge pages quickly, but we explicitly take time back for after-hours incident response, and managers make sure their reports actually do so. Missed pages are never counted against performance reviews. The policy exists to ensure coverage, not to penalize us for having lives outside of work. Our leadership reinforces this directly. We're expected to work hard given the scale of opportunity in front of us, but we're intentional about not expecting excessive hours. Instead, we focus on working smart, moving fast, and tackling ambitious problems together.

We operate on four core values: seek and value feedback, build iteratively, communicate broadly and often, and everyone is an owner. We consider ourselves owners of production, not just code, treating our systems like our own home rather than a hotel room we're renting. When things go wrong, we run blameless postmortems focused on fixing systems, not assigning blame. That sense of care extends to how we treat each other. There's genuine compassion within our team and toward candidates coming through our hiring pipeline, which many of us say sets Rula apart from other places we've worked. Working on a mental health mission has a way of shaping how we collaborate, with more empathy, patience, and genuine investment in getting it right together.

We offer a formal mentorship program and dedicated career development resources introduced during onboarding, along with a biweekly Tech Talk series where we share new technologies and ideas. Our collaborative, idea-sharing culture creates a strong environment for learning and growth, and we regularly work through technical tradeoffs together rather than in isolation. 
Growth here also means developing our craft, not just advancing our titles. We're encouraged to experiment, make frequent iterative improvements rather than rely on large one-time releases, prototype and demo ideas quickly, and embrace tools like AI to enhance how we work.

We put new engineers through a structured first-90-days onboarding path: week one is orientation and dev environment setup, week two is shipping a first bugfix or small feature, and by weeks three and four new hires are shipping medium-sized tickets. Our onboarding progresses from team-specific ramp-up in month one, to a broader view of our engineering org's architecture and roadmap in month two, to participating in org-wide programs like mentorship and interview training in month three. We keep learning going through a biweekly Tech Talk series, where any of us can present on technologies, best practices, or demos, plus a dedicated mentorship program and a growing library of engineering documentation and guides.

We're evolving our architecture toward more independent, event-driven services specifically to reduce our dependence on legacy third-party systems. That gives us the opportunity to modernize our core infrastructure, not just build on top of it.

We're also growing our investment in AI. Our AI engineering team gets the best of both worlds, combining the stability and reach of an established organization with the energy and greenfield opportunities of an AI startup. We're building AI-powered support across the full therapy journey, from helping patients find the right provider to assisting clinicians with pre-session preparation, always with the goal of augmenting the human connection at the center of care rather than replacing it.