Staff Software Engineer, Growth

Brightside Health

1d•$175,000 - $225,000•Remote

About The Position

Brightside is looking for a Full-Stack Staff Software Engineer, Growth with a strong product sense who values a high degree of autonomy. You will be collaborating closely with Product, Design, and Marketing to continue the rapid iteration of our top of funnel and intake funnel that allows us to continue expanding Brightside’s reach. This team is responsible for member growth, including optimization of the purchasing funnel and conversion of prospects to Brightside members through technological excellence and innovation. This includes executing on strategic third party partnerships in support of driving referrals from other entities. What you’ll be doing as Staff Software Engineer, Growth: A successful Staff Engineer on this team does more than write excellent code - they improve the patient experience and drive meaningful business outcomes. In practice, that means: Identifying the highest-leverage opportunities across care discovery, mental health assessment, and provider booking experiences. Connecting technical investments to measurable patient, operational, and business outcomes. Using data to uncover friction points, understand system performance, and validate the impact of solutions. Building platforms, tooling, and automation that enable cross-functional teams to move faster and make better decisions. Simplifying complex intake and care-matching workflows while accounting for the realities of healthcare, insurance, and compliance. Raising the technical bar by helping other engineers make sound architectural and implementation decisions. Creating clarity and alignment in ambiguous problem spaces. Delivering solutions that are reliable, observable, scalable, and maintainable. Identifying opportunities to leverage AI, agents, and automation to reduce operational overhead, improve decision-making, and streamline complex workflows. Championing a culture of experimentation by using A/B testing and data-driven learning to guide product and engineering decisions.

Requirements

Significant experience shipping production software, typically gained over 10+ years or through equivalent high-impact experience.
Strong fluency with Ruby on Rails and modern TypeScript/React.
Solid relational database experience, including schema design, query performance, data modeling, and safe migrations.
Experience integrating with external APIs in production, including retries, idempotency, rate limits, partial failures, observability, and vendor quirks.
A track record of operating autonomously on ambiguous, cross-functional problems.
Strong product judgment: you can reason about user needs, operational workflows, edge cases, and tradeoffs.
Strong data instincts: you can use metrics, logs, database queries, dashboards, and product analytics to understand what is happening and whether a change helped.
Demonstrated ability to raise the bar of a team through code review, design review, mentorship, technical writing, or pattern-setting.
Excellent written communication, including design docs, RFCs, incident write-ups, rollout plans, and clear decision records.
Comfort working in regulated or high-trust systems where correctness, privacy, and auditability matter.
Comfort using AI-native development practices, including AI coding tools, agents, and automation to accelerate high-quality software delivery.

Nice To Haves

Experience with modularized monoliths, Packwerk, CQRS, event-driven systems, or service boundaries inside larger applications.
Familiarity with HIPAA, PHI handling, SOC 2, or other regulated-industry constraints.
Experience designing AI-assisted workflows, especially where human review, auditability, and safety matter.

Responsibilities

Identifying the highest-leverage opportunities across care discovery, mental health assessment, and provider booking experiences.
Connecting technical investments to measurable patient, operational, and business outcomes.
Using data to uncover friction points, understand system performance, and validate the impact of solutions.
Building platforms, tooling, and automation that enable cross-functional teams to move faster and make better decisions.
Simplifying complex intake and care-matching workflows while accounting for the realities of healthcare, insurance, and compliance.
Raising the technical bar by helping other engineers make sound architectural and implementation decisions.
Creating clarity and alignment in ambiguous problem spaces.
Delivering solutions that are reliable, observable, scalable, and maintainable.
Identifying opportunities to leverage AI, agents, and automation to reduce operational overhead, improve decision-making, and streamline complex workflows.
Championing a culture of experimentation by using A/B testing and data-driven learning to guide product and engineering decisions.