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DISCO

Enterprise AI Platform Engineer

Austin, TXmidAdded 1 month ago

About this role

Transform AI prototypes from the innovation lab into secure, scalable enterprise systems. This role bridges experimental development and production engineering, handling re-architecture, cloud deployment, security implementation, and developer enablement across the organization.

What you'll do

  • Re-architect AI prototypes for production deployment with cloud infrastructure design (AWS/Azure), CI/CD pipelines, containerization, and monitoring
  • Implement security and compliance measures including secrets management, encryption, audit logging, and regulatory validation
  • Design scalable architectures supporting 1,000+ users and establish engineering standards and best practices
  • Mentor non-engineering teams, conduct code reviews, and provide troubleshooting support for prototype solutions
  • Build internal developer platforms and infrastructure-as-code templates to accelerate development
  • Train teams on DevOps practices and create technical documentation for stakeholders

What they're looking for

  • Python and TypeScript/JavaScript development
  • Cloud platforms (AWS/Azure)
  • Kubernetes and Docker containerization
  • CI/CD pipeline tools (GitHub Actions, Jenkins)
  • Infrastructure-as-Code (Terraform/CloudFormation)
  • RESTful API design and integration patterns
  • Database technologies (PostgreSQL, Redis, NoSQL)
  • Cloud security and observability tools

Benefits

  • Medical, dental, and vision insurance
  • 401(k) retirement plan
  • Competitive salary plus RSUs
  • Flexible PTO
  • Collaborative, inclusive work environment
  • Growth opportunities within 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 a time you re-architected a prototype or MVP into a production system. What were the biggest challenges in scaling it for enterprise use?
  • Describe your experience designing and implementing CI/CD pipelines. Which tools have you used, and how have you optimized them for reliability and speed?
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