K2 is building the largest and highest-power satellites ever flown, unlocking performance levels previously out of reach across every orbit. Backed by over $1 billion in total funding from leading investors including Altimeter Capital, ICONIQ, Kleiner Perkins, Lightspeed Venture Partners, Redpoint Ventures, and T. Rowe Price — and with over $1 billion in signed contracts across commercial and US government customers, we're mass-producing the highest-power satellite platforms ever built for missions from LEO to deep space.
The rise of heavy-lift launch vehicles is shifting the industry from an era of mass constraint to one of mass abundance, and we believe this new era demands a fundamentally different class of spacecraft. Engineered to survive the harshest radiation environments and to fully capitalize on today's and tomorrow's massive rockets, K2 satellites deliver unmatched capability at constellation scale and across multiple orbits.
With multiple launches in 2027 and plans to scale to 100 satellites a year, we're Building Bigger — helping develop the solar system and build toward a Kardashev Type II (K2) civilization. If you are a motivated individual who thrives in a fast-paced environment and you're excited about contributing to the success of a high-growth Series D-funded company, we'd love for you to apply.
The Role
The Enterprise Information Systems (EIS) team builds the digital backbone behind K2's satellite design, manufacturing, and mission operations, connecting engineering, production, and mission control so our hardware moves from concept to orbit faster. We're looking for a Platform Engineer who believes developer experience is a first-class engineering discipline. You'll build the deployment patterns, guardrails, and tooling that let engineers from many backgrounds, including those building with AI assistance, ship secure, reliable applications with minimal friction.
Responsibilities
- Build and maintain golden-path deployment patterns for Amazon EKS, with built-in guardrails that get applications to production faster.
- Help drive secure, consistent AI adoption across software development, including guardrails, governance, observability, and operational support for AI-assisted workflows.
- Build automated policies and CI/CD gates that enforce code quality, test coverage, and safe deployments.
- Integrate end-to-end monitoring, alerting, and SLOs into the platform.
- Track performance and cost (latency budgets, cross-AZ transfer, IP consumption, load balancer efficiency) and act on anomalies.
- Write approachable docs and diagnostics, such as guides, diagrams, and "why can't this connect?" flows, that shorten support loops.
