Austin, TX Hybrid Full-time

Future Secure AI is hiring a Platform DevOps Engineer

Responsibilities

  • Design and manage stable infrastructure to support AI-powered applications in production environments
  • Take ownership of Kubernetes platforms that run AI-driven workloads
  • Develop and manage infrastructure using code through Terraform configurations
  • Create and sustain Helm-based processes for application deployment
  • Establish, track, and enhance system reliability using service level indicators, objectives, and agreements
  • Engage in on-call duties, incident management, root cause investigations, and post-incident reviews
  • Minimize manual operational tasks by implementing automation and system improvements
  • Enhance system observability through monitoring, log management, and alerting frameworks
  • Collaborate closely with software engineers to ensure systems are resilient, scalable, and secure
  • Support all phases of the software lifecycle, including build, deployment, and operations
About company
Future Secure AI

We have a distinctive, proven approach for fast, high-ROI deployment of AI in enterprises:

  • We build bespoke AI Co-Workers for the Red Zone. They consist of a persona wrapped over a complex multi-agent system to undertake controlled, context-specific workflows with enterprise grade security and high ROI (vs simpler Blue-Zone agentic tools)
  • We rely on a new collaborative approach to AI design, build and run with our customers: one that’s a true partnership, not SaaS, not black boxes, not systems integration or consulting
  • We have proven experience driving fast ROI impact in large, complex organizations, and are agnostic to cloud infrastructure and LLMs with the ability to easily integrate third-party agents and systems

We focus on Red-Zone (i.e., higher complexity) use cases. Our AI Co-Workers are fast and responsive at scale, orchestrate large numbers of advanced agents, enable highly secure task and process execution and deliver observability that mission-critical enterprise workflows require. We sit below the expensive private data and ML Black-Zone players; and we sit well above the myriad Blue-Zone plug-and-play agentic players who often fail to deliver more complex, context-specific workflows.

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Job Details
Category infrastructure
Posted 3 hours ago