About Evidation
Evidation creates new ways to measure and improve health in everyday life—making proactive, personalized, and truly human-centered healthcare possible. By connecting directly with millions of individuals, Evidation harnesses real-world data to deeply understand health experiences, rapidly and at scale. Evidation’s privacy-centric digital health measurement and engagement platform uses data science and machine learning to translate these everyday insights into high-impact health guidance, treatments, and tools. Founded in 2012, Evidation is headquartered in California with employees working around the globe.
About the role
We’re seeking a Staff Engineer to work on-site in Santa Barbara - someone who genuinely values being in-person, working side-by-side and building things together. The successful candidate will be equally comfortable architecting complex systems and diving deep into implementation. This isn’t a traditional full stack role—it’s for an engineer who is fully committed to integrating AI Agents, automation, and AI-driven tooling into both their own workflow and the broader engineering practice.
As a Staff Engineer, you’ll set the standard for how AI-augmented engineering is done: solving hard problems across the stack, accelerating development velocity, and mentoring others to adopt AI-first ways of working.
What you'll do
- Technical Leadership
- Lead design and architecture across backend (Ruby on Rails), frontend (Expo/React Native), and infrastructure.
- Provide deep technical expertise, guiding teams through complex architecture, trade-offs, and long-term technical investments.
- Drive the technical vision and strategy in alignment with company goals.
- Take ownership of critical technical areas, ensuring projects are delivered with quality and speed.
- Set and uphold high engineering standards, ensuring scalability, reliability, and maintainability in system design.
- Mentor engineers on both technical depth and effective use of automation.
- AI-Driven Development
- Define and champion best practices for AI-first engineering workflows.
- Experiment with and integrate AI tools into the software development lifecycle: design, coding, testing, deployment, and operations.
- Build frameworks and libraries that make AI-assisted development a repeatable, scalable practice.
- Reduce engineering toil by leaning on automation and AI-driven observability.
- Product & Platform Execution
- Collaborate closely with product, design, and data teams to deliver measurable outcomes.
- Communicate complex technical concepts clearly to both technical and non-technical audiences.
- Build consensus across teams, fostering collaboration and alignment in technical decisions.
- Anticipate organizational technical needs and propose solutions that address company-wide challenges.
- Ensure reliability, scalability, efficiency and security of our solutions.
Qualifications
- Technical Expertise
- 12+ years professional experience in software engineering with proven full stack capability.
- Deep knowledge of Ruby on Rails and Expo/React Native.
- Experience with automated testing (Playwright, Postman, or equivalent) and integrating tests into CI/CD.
- Proficiency with CI/CD pipelines (GitHub Actions or similar).
- Strong grasp of distributed systems, REST/GraphQL APIs, and modern cloud architectures (AWS).
- AI Enthusiasm & Practice
- Hands-on experience with AI-assisted coding and automation tools.
- Eagerness to stay on the bleeding edge of AI development trends (prompt engineering, agent-based workflows, automated testing).
- Ability to influence teammates in adopting AI-first practices.
- Leadership & Influence
- Track record of driving architectural decisions or leading technical initiatives.
- Ability to mentor engineers and set technical direction across projects.
- Strong communication skills to work effectively across engineering, product, and leadership.
Nice to Haves
- Infrastructure as Code (IaC): Pulumi / Go
- Experience building dynamic infrastructure beyond Terraform.
- Data & Analytics: dbt + Snowflake
- Experience with modern data transformations (dbt) and cloud data warehouses (Snowflake).
- Containerization & Orchestration: EKS + Helm
- Familiarity with deploying and managing services in Kubernetes (EKS).
- Experience with Helm for repeatable deployments and release management.