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Skills
Application Programming Interface (API)unmatched
Architectural Designunmatched
Artificial Intelligence (AI)unmatched
Beveragesunmatched
Biologyunmatched
Biotech and Pharmaceuticalunmatched
Building Systemsunmatched
Cloud Computingunmatched
Code Reviewsunmatched
Cost Controlunmatched
Cross-Functionalunmatched
Data Setsunmatched
Debugging Skillsunmatched
Distributed Computingunmatched
Drug Discoveryunmatched
Environmental Impactunmatched
Establish Prioritiesunmatched
Human Diseasesunmatched
JavaScriptunmatched
Mentoringunmatched
MongoDBunmatched
NoSQLunmatched
Node.jsunmatched
Operating Systemsunmatched
Pharmacovigilanceunmatched
PostgreSQLunmatched
Problem Solving Skillsunmatched
Programming Toolsunmatched
Research Skillsunmatched
Scientific Researchunmatched
Software Engineeringunmatched
Startupunmatched
System Operationsunmatched
Systems Scalabilityunmatched
Technical Leadershipunmatched
Description
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