Jobs Companies Deep Origin Staff Full Stack/Back End Engineer (NodeJS)

À propos de ce poste Staff Full Stack/Back End Engineer (NodeJS) chez Deep Origin

Deep Origin · Sur site · South San Francisco, California, United States

About Deep Origin

Deep Origin is a biotech startup building an operating system for science that transforms how life science research is conducted. Led by Michael Antonov, co-founder of Oculus, and backed by Formic Ventures, we are redefining the infrastructure behind modern drug discovery. Our AI-driven platform enables scientists to accelerate discovery, reduce cost, and bring breakthrough innovations to life faster. As we scale, overall excellence is a critical lever in advancing our mission to dramatically reduce disease and extend human healthspan.

Role Description

We are seeking a talented and experienced Staff Engineer to join our dynamic team. You will be a key member of the software engineering team, building our key functionality and integrating with key partners. You will have ownership in key software feature areas and their architectural design, as well as software implementation with a high level of independence and impact. You will work closely with cross-functional teams to create robust, user-friendly services and applications that drive the efficiency and effectiveness of biologists and researchers in their scientific endeavors.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Requirements

  • 10+ years designing, building, and operating complex, highly scalable distributed systems
  • 5+ years hands-on with TypeScript/JavaScript, and Node.js
  • Strong experience with both relational (e.g. Postgres) and NoSQL (e.g. MongoDB) data stores
  • Experience building platforms from an early stage and scaling them to high load (10,000+ DAU)
  • Experience designing and operating multi-tenant systems with complex datasets and relations
  • Staff-level technical leadership: setting direction across teams, driving design reviews, mentorship and code review
  • Fluent with AI-assisted development tools (e.g. Claude Code, Cursor), applying them to accelerate delivery without compromising code quality or architecture
  • Systematic problem-solver with a strong sense of ownership, effective independently and on a team
  • Experience in high-energy startups with fast delivery cycles
  • Must work onsite at least 3 days a week


Nice to have

  • Hands-on Kubernetes and cloud infrastructure experience, including cluster operations and operators
  • Experience with scientific, biotech, or research-heavy data platforms

Responsibilities:

  • Own the architecture and delivery of major systems, from design to production, prioritizing sound long-term design over short-term implementation
  • Build production services that handle complex scientific data at scale, with clean APIs and solid testing
  • Set technical direction across teams and lead design reviews
  • Operate distributed systems on Kubernetes with an eye on reliability, performance, and cost
  • Turn rough requirements from product and science teams into robust implementations
  • Debug across the full stack, from app logic to production workflow failures
  • Raise the bar through code review and mentorship
  • Set the standard for AI-assisted engineering

Values & Working Style

  • Ownership mindset — you take responsibility for building systems that redefine how drug safety is evaluated
  • Comfortable navigating ambiguity in a fast-moving, high-impact environment
  • Strong collaboration across science, engineering, and business teams

Benefits

  • Competitive compensation package with meaningful equity
  • Comprehensive health, dental, and vision coverage
  • Annual team gatherings and company events
  • Free lunch, snacks, beverages, and onsite gym access (for in-office employees)
  • Opportunity to shape the future of health, longevity, and our ability to simulate life.
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À propos de Deep Origin

We are building tools that help scientists solve disease. Streamline computational analysis today. Simulate biology tomorrow.

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