Sr. Software Systems Safety Engineer

About the role

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.

We operate at the cutting edge of Applied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.

JOB SUMMARY

Own the safety assurance of the software and AI that run our humanoid robots, from architecture analysis through verification evidence. You will analyze software and AI safety architectures, lead the safety analyses, and assess whether the evidence supports our safety claims. You will draw on IEC 61508-3, ISO/IEC TS 22440, and deep experience with safety-critical software systems.

ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES

- Collaborate on system-level risk assessments, allocate risk reduction measures to software and AI elements, and own the breakdown of software-domain safety requirements into subsystem and element-level requirements

- Analyze and define the software safety architecture, including partitioning and freedom from interference, watchdogs, diagnostics, plausibility and timing monitoring, communication integrity, startup/shutdown behavior, and fault handling

- Lead software safety analyses, including software FMEA, fault tree analysis, dependent/common-cause failure analysis, and timing and resource analysis

- Specify safety-related software behavior, such as monitors, diagnostics, and safe-state logic, and review software team designs against IEC 61508-3 requirements for the target SIL / SC

- Define the IEC 61508-3 software safety plan and lifecycle, and assess team conformance through reviews and audits, including existing in-house, open-source, and third-party libraries, RTOS, and middleware

- Assess software systematic capability and review verification evidence, including coverage, static analysis, fault injection, and software-in-the-loop and hardware-in-the-loop test results, for adequacy against safety claims

- Apply the AI safety lifecycle (ISO/IEC TS 22440) to AI/ML-enabled functions, defining the safety architecture around them, including independence of safety functions from learned components and the safety mechanisms that monitor them

- Assess AI/ML safety evidence against the AI safety lifecycle, including data and model assurance, performance limitations, and operational design domain

- Own software requirements traceability and the software portion of the safety case, including gap assessments against standards

- Support product safety and compliance teams in certification and demonstration of standards conformity