Senior Software Engineer (AI Series A Healthtech)

Craniometrix has raised over $21 million to help make dementia suck less. Dementia is tough – but it can be easier. Turns out, if you give families the right non-clinical coaching and support, you can avoid 30% of hospitalizations for these patients. And Medicare has recently started paying for that coaching. We launched our care navigation service for dementia patients in July of 2025, leveraging AI to provide best-in-class care, allowing us to quickly hit $8M of ARR and raise a $15M Series A. We have an incredibly exciting product opportunity ahead of us. While we provide a human service (and always will), our business is ripe for automation — only 25% of the care team’s time is actually with patients. That number should be 75%. Getting there means applying cutting-edge AI to automate care. And because we are an internal product company, you can build quickly and deploy quickly, iterating rapidly in a way almost no other engineering orgs at healthcare companies can. Like almost every great engineer in the AI age, this will also be an IC role that goes beyond engineering — this role is a strong fit for an engineer who has good product taste, moves with agency, and is comfortable wearing many hats in a fast-moving environment. We care a lot about people who can operate independently, make good product decisions, and are genuinely on the cutting edge of AI-enabled software development. You should already be using AI deeply in your day-to-day workflow, whether for exploring solutions, scoping work, writing and refactoring code, debugging issues, improving tests, or accelerating iteration without lowering the quality bar. We are especially excited about engineers who actively seek out new tools and workflows, separate signal from hype, and turn the best new AI capabilities into real execution leverage. What You’ll Do Own features end-to-end across the full development lifecycle, including scoping, implementation, code review, deployment, and iteration Build across the stack using React and NodeJS to ship product improvements that make our internal teams more effective Work directly with the Operations team, including care navigators, to understand friction points and improve the tools they use every day Monitor production through metrics, logs, and Sentry, identify issues quickly, and drive fixes through to resolution Take clear ownership of the product in production: you build it, you monitor it, you improve it Help raise the quality bar for engineering, product thinking, execution, and modern AI-assisted software development as we continue to grow Use AI deeply across the engineering workflow, including planning, implementation, debugging, code review, testing, and incident response Stay current with the rapidly evolving AI tooling landscape and bring practical new workflows, patterns, and tools into the team when they meaningfully improve speed or quality What We’re Looking For 5+ years of professional software engineering experience Strong experience building product features across the stack Hands-on experience with React and NodeJS Strong product taste and good judgment about what makes a product useful, clear, and high quality High autonomy, agency, and comfort operating with ownership in a small team Strong communication and collaboration skills across engineering, product, and operations Deeply comfortable using AI as part of your engineering workflow, and excited to stay at the frontier of how great engineers use it in practice Strong judgment about when AI increases speed and quality, and when deeper manual thinking or validation is needed Curiosity and enthusiasm for adopting new AI tools and workflows early, with the discernment to focus on what is actually useful Excited to work in a fast-paced startup environment where priorities can evolve and everyone contributes beyond a narrow job description Preferred Qualifications Experience with Postgres Experience in a startup environment Experience in healthcare or other operationally complex or regulated environments A track record of thoughtfully adopting new AI tools or workflows to improve engineering velocity, quality, or leverage