Technical Depth and Rigor
You have demonstrated the ability to reason through complex systems and make sound engineering decisions. That evidence might come from:
- Designing and shipping production systems
- Building products from 0 to 1 in ambiguous environments
- Research, open-source contributions, or other technically rigorous work
- Solving problems that required thoughtful system design, tradeoff analysis, or non-obvious technical decisions
You are comfortable reasoning from first principles, when necessary, rather than relying solely on established patterns.
We care more about how you think and build than whether your background follows a traditional path.
Startup Adaptability
We are a mid-stage startup. Priorities evolve. Documentation is not always perfect. Sometimes the best path forward is not immediately obvious.
We are drawn to engineers who:
- Thrive in environments with evolving structure
- Take ownership of learning new systems and domains
- Proactively identify next steps rather than waiting for assignments
- Stay anchored to business goals, not just technical elegance
Ownership, Pace, and Judgment
Strong candidates demonstrate:
- Clear reasoning behind architectural decisions
- Ability to articulate tradeoffs, not just best practices
- Awareness of business context when estimating timelines
- The discipline to meet commitments
- The judgment to increase intensity when the situation calls for it and to simplify when complexity is not justified
We value engineers who understand that great software supports real business outcomes.
Breadth and Curiosity
We appreciate engineers who:
- Have expanded their scope over time through new systems, domains, or increased responsibility
- Are comfortable stepping slightly outside their core area when needed
- See product, customer impact, and technical design as interconnected
Deep specialists are welcome, especially those who have increased complexity and ownership within their domain.
Experience That Is Particularly Relevant, Not Required
Exposure to complex or real-world data problems is compelling, including:
- Systems interacting with physical processes
- Geospatial or spatial data
- Combining multiple data streams to infer meaningful signals
- Problems requiring modeling, interpretation, or non-obvious conclusions
Strength in some areas can compensate for gaps in others.
