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Planet

Software Engineer

San Francisco, CAFrom $180.6kfull-timemidAdded yesterday

About this role

Planet Labs seeks an experienced Software Engineer to lead enterprise AI application deployment, building production-ready systems using Gemini and Claude while managing AI infrastructure, governance, and compliance in a regulated environment. You'll architect AI gateways, agent registries, and intelligent workflows while ensuring adherence to ITAR/EAR standards across the organization.

What you'll do

  • Design and deploy production Enterprise AI applications using Gemini Enterprise Agent Platform and Claude
  • Build and maintain centralized AI Gateway for LLM API routing, rate limiting, and cost management
  • Develop AI Agent Registry to catalogue, govern, and monitor agents company-wide
  • Implement logging, monitoring, and alerting frameworks for AI system tracking
  • Manage AI data pipelines and infrastructure compliant with ITAR and EAR standards
  • Collaborate with Security and Legal on data access controls, secret management, and compliance for AI integrations

What they're looking for

  • Python
  • GCP and AWS
  • SQL and Vector Databases
  • AI Gateways and orchestration platforms
  • AI Agent Registries
  • Regulated compliance standards (ITAR, EAR, FedRAMP)
  • Gemini Enterprise App
  • Claude and Cursor

Benefits

  • Comprehensive Medical, Dental, and Vision coverage
  • Health Savings Account with company contribution
  • Generous Paid Time Off plus holidays
  • 16 weeks Paid Parental Leave
  • Home Office and phone/internet reimbursement
  • Tuition reimbursement and LinkedIn Learning access
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Planet

Planet builds and operates Earth-imaging satellites and the cloud-native platforms that process satellite imagery data. The company is hiring software engineers for platform operations and backend compute systems, as well as hardware engineers (opto-mechanical and electrical) to design satellite payloads and subsystems.

View all jobs at Planet

Likely interview questions

  • Describe your experience building and deploying AI applications in regulated environments—how did you approach ITAR/EAR compliance?
  • Tell us about a time you designed an AI Gateway or similar infrastructure to manage LLM APIs at scale.
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