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DISCO

Enterprise AI Platform Engineer

United StatesmidAdded yesterday

About this role

Transform AI prototypes into production-grade enterprise systems by architecting secure, scalable infrastructure on cloud platforms. Bridge the gap between innovation labs and operations through platform engineering, DevOps practices, and developer enablement.

What you'll do

  • Re-architect Python and AI prototypes into secure, scalable enterprise deployments with cloud infrastructure design (AWS/Azure), CI/CD pipelines, and containerization
  • Implement security measures including secrets management, encryption, audit logging, and ensure compliance with enterprise policies and regulatory standards
  • Design production-ready architectures for 1,000+ users, establish engineering standards, and create technical documentation
  • Build internal developer platforms and infrastructure-as-code templates to accelerate development across teams
  • Mentor non-engineering teams through code reviews, troubleshooting, and DevOps training
  • Set up comprehensive monitoring and observability for all production AI systems

What they're looking for

  • Python and TypeScript/JavaScript
  • AWS/Azure cloud infrastructure and architecture
  • Docker and Kubernetes containerization
  • CI/CD pipelines (GitHub Actions, Jenkins)
  • Infrastructure-as-Code (Terraform, CloudFormation)
  • RESTful API design and integration patterns
  • Security and secrets management
  • Relational and NoSQL databases (PostgreSQL, Redis)

Benefits

  • Medical, dental, and vision insurance
  • 401(k) retirement plan
  • Competitive salary plus RSUs
  • Flexible PTO
  • Open, inclusive, and collaborative environment
  • Growth opportunities throughout the company
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DISCO

DISCO builds a SaaS legal tech platform that helps organizations manage legal data and documents. The company is hiring DevOps, infrastructure, and compliance engineering roles to scale its cloud infrastructure, implement secure enterprise systems, and automate compliance across AWS-based environments.

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Likely interview questions

  • Walk us through your experience transitioning an MVP or prototype to a production system—what were the biggest challenges and how did you address them?
  • Describe your approach to designing a scalable cloud architecture on AWS or Azure for an application expected to serve 1,000+ users.
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