Staff Software Engineer

Who We Are

We are a fast-growing vertical SaaS company leveraging innovation and disruptive technologies to improve consumer experiences, outcomes, and predictability within the plastic surgery industry. Our team thrives on challenges, embraces change, and is dedicated to transforming how the industry operates.

Our platform is what aesthetic medicine and plastic surgery practices run their business on, covering scheduling, clinical records, forms and consents, invoicing and payments, patient communications, and the marketing that sits in front of all of it. It is a multi-tenant platform holding millions of patient records under HIPAA and GDPR, and we onboard new practices every month.

Who We're Looking For

We are builders. An engineer here owns a whole problem, from the first conversation to production. We build with AI as the default: coding agents draft fast, and knowing what to build and what is wrong with the draft is the skill we hire for and level on.

We are hiring a Staff Software Engineer to change that. Staff at Adoreal means expert, discover, lead, and the bar is absolute: you would be recognized as Staff at any strong engineering company, and the level travels with you.

The work in front of you is concrete. A .NET estate of roughly 80 repositories to bring onto .NET 8 against a hard support deadline. Tenant isolation in a HIPAA platform that needs to be made provably right, not just believed to be. A CI pipeline that costs eighteen minutes a change and should cost a fraction of that. AI features, including an ambient clinical scribe, moving from pilot to product. Tell us which of these you would take first.

Responsibilities

Architecture across teams

• Own cross-team initiatives problem to production, including the parts nobody else claims.
• Own architecture across teams and find the simplifications that remove whole classes of work and defects, including the systemic friction of shared repositories, environment contention and queue bottlenecks.
• Design the quality architecture across teams: gate standards, observability baselines, safe-migration patterns. Find systemic quality risks before they find us.

Building with AI, and building AI

• Define how Adoreal engineers with AI across the organization: the workflows, the shared infrastructure, and the verification practices other teams adopt, holding AI-drafted work to the same review bar as any other.
• Evaluate emerging capability on a regular rhythm, measure its real impact, and retire what stops earning its place.
• Ship AI into the product: clinical documentation, patient communication, and the intelligence our clinics' data makes possible, built to HIPAA and GDPR standards from the first design.

Multiplying the organization

• Mentor senior engineers, shape the hiring bar, and be a go-to across the organization.
• Take the hardest reviews in the codebase, and teach through them rather than gate.
• Partner with product leadership so that the systems you design are built for where the business is going, not where it has been.