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Salary
≈ $52k – $87k per year (Estimated)
Location
Hybrid (Paris, France, London, United Kingdom)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 26, 2026. First seen by Alion on Apr 30, 2026. Genesis AI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Headquartered in Palo Alto, California, and Paris, France, Genesis AI is a full-stack physical AI and robotics company specializing in universal foundation models and general-purpose robotic systems. The company develops advanced technologies, including the GENE foundation model and human-scale dexterous hands, to enable automated physical labor. Through its innovative hardware and software ecosystem, its systems are engineered to perform complex, real-world tasks across various industrial and commercial environments.

What You'll Do

  • Take on ambiguous reliability, scalability, and efficiency challenges and drive solutions across SRE and development teams.

  • Build and run large-scale, massively distributed, fault-tolerant systems that keep Genesis platform reliable and performant for our customers.

  • Optimize existing systems, build infrastructure, and eliminate toil through automation to continuously improve uptime and rate of change.

  • Cultivate a culture of reliability throughout the organization, guiding technical decisions that balance system health with fast-moving product priorities.

  • Ensure the long-term health, maintainability, and reliability of services through capacity planning, performance analysis, and proactive incident prevention.

What You'll Bring

  • Strong software engineering skills (e.g., in Python, Go, or similar) with extensive experience designing, analyzing, and troubleshooting distributed systems.

  • Deep expertise with cloud computing platforms (e.g., Kubernetes, Cloud Functions) and Non-Abstract Large Systems Design (NALSD).

  • Experience leading complex, large-scale technical projects and providing technical leadership across teams.

  • Ability to apply coding, algorithms, and complexity analysis to solve ambiguous problems at scale with minimal disruption.

  • A collaborative, intellectually curious mindset - comfortable working across a wide variety of backgrounds and bringing cross-team perspective to build robust, reusable solutions.

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