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Figure

Software Engineer, Privacy & Data Governance

San Jose, CA$150k–$350kmidAdded 1 month ago

About this role

Figure, an AI robotics company building humanoid robots, seeks a Software Engineer to lead privacy and data governance initiatives for their products and backend services. You'll design privacy-first architecture, implement data protection systems, and ensure regulatory compliance across the technology stack, requiring 5 days/week on-site collaboration in San Jose.

What you'll do

  • Design and implement privacy-by-design features embedding data minimization and privacy controls into product architecture
  • Develop core privacy engineering services for user control, anonymization, and data lifecycle management
  • Collaborate with AI, engineering, and security teams to enforce data governance and protection practices
  • Create custom tools, APIs, and libraries to standardize privacy enforcement and monitor compliance
  • Translate privacy requirements into technical specifications and scalable solutions with stakeholders
  • Advocate for user privacy and security across the organization

What they're looking for

  • Privacy engineering (anonymization, de-identification, data governance)
  • Software development in C/C++, Rust, Golang, or Python
  • API and microservices architecture
  • Data protection and privacy-by-design principles
  • Data retention, deletion, and lineage management
  • Collaboration and stakeholder communication
  • Regulatory compliance knowledge
  • Embedded systems experience

Benefits

  • Competitive salary range $150,000 - $350,000 annually
  • Additional compensation components based on individual factors
  • Full-time position with benefits package
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Figure

Figure develops advanced humanoid robots powered by AI technology. The company is hiring engineers across mechanical design, firmware development, manufacturing, quality assurance, and security to build and refine its autonomous robotic systems.

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Likely interview questions

  • Walk us through a privacy-by-design implementation you led. How did you embed privacy controls into the architecture from the start rather than bolting them on later?
  • Describe your experience building APIs or microservices specifically for data governance or privacy enforcement. What challenges did you face scaling them across multiple teams?