Staff Robot Intelligence & Integration Engineer

Knightscope•Sunnyvale, CA

6d•$240,000 - $275,000•Onsite

About The Position

In this role, you will define how K7 perceives, reasons about, and responds to security threats to make our world safer. Drawing on embodied AI principles, you will be a technical lead working across robotics, systems integration, and cloud engineering to ship the autonomy contract layer: the canonical event model, the reasoning policy, and the evidence integrity chain that make K7 not just an observer but a reliable, auditable actor in the field.

Requirements

7+ years of hands-on experience at an OEM, AV company, physical security platform, or robotics tech company shipping autonomy or systems integration software to production.
Strong systems architecture skills: canonical API and event-driven pipeline design, distributed store-and-forward, and schema-governed message contracts.
Hands-on cloud-to-robot integration experience, message brokers, deduplication, replay-safe ingest, and understanding of graceful degraded-mode design.
Solid understanding of robotics control loops, motion planning interfaces, and the boundary between advisory autonomy and deterministic safety-critical control, with hands-on experience in state machines, behavior trees, or safety arbitration layers.
Strong C++ and Python; experience with ROS2 and mission-state machine design.
Production-first mindset, demonstrated ability to define and enforce interface contracts between hardware-side and cloud-side teams.

Nice To Haves

MS or PhD in Robotics, Computer Science, Systems Engineering, or related field.
Exposure to embodied AI concepts or systems: unified perception-reasoning-action architectures, foundation models for robot control, or end-to-end policy learning in deployed autonomous platforms.
Familiarity with functional safety standards, ISO 26262 or SOTIF, particularly as they apply to the boundary between advisory autonomy and deterministic safety-critical control.
Experience building data flywheel pipelines for safety-critical ML systems.
Familiarity with evidence integrity and chain-of-custody requirements for security or legal contexts.

Responsibilities

Own the full intelligence-to-action loop: from K7's raw detection stream through entity reasoning, world-state modeling, and incident hierarchy, to policy decisions that drive safe, bounded robot behavior.
Design and maintain the canonical event contract: a single, normalized message shape across all detection types that feeds the cloud incident system, versioned and replay safe.
Interface the autonomy policy layer with the motion planning stack: define what the intelligence layer can recommend, what the safety arbiter validates, and what gets passed to controls for execution.
Build the closed-loop learning pipeline: operator outcomes, incident dispositions, and retained evidence feed model evaluation and retraining without modifying the safety boundary
Drive technical decisions on architecture, integration contracts, and roadmap; mentor engineers across the team.