Staff DevOps Engineer/SRE

The FlexAI Compute Infrastructure Platform provides an "end-to-end AI compute layer" for running and managing workloads across any cloud, any GPU, and any deployment model (public, hybrid, or on-prem). It brings together "1-click simplicity" for users with "enterprise-grade orchestration, security, and automation" under the hood.

FlexAI is looking for a Staff DevOps / SRE Engineer to define our infrastructure strategy, establish SRE best practices, and build systems capable of running large-scale AI workloads across distributed, multi-cloud environments.

You’ll work closely with developers to ensure our platform is reliable, performant, and scalable — without slowing down product velocity.

• Design and evolve the infrastructure backbone for our AI and PaaS platform
• Build highly available, fault-tolerant, and scalable systems
• Define and drive SRE practices (SLIs, SLOs, error budgets)

• Lead Infrastructure as Code using Pulumi
• Own and scale Kubernetes clusters and containerized workloads
• Standardize and automate infrastructure for global deployments

• Design and scale CI/CD pipelines for fast, reliable releases
• Build self-healing systems and automated remediation workflows
• Drive GitOps and platform engineering practices

• Implement end-to-end observability using VictoriaMetrics and Grafana (metrics, logs, traces)
• Identify and resolve performance bottlenecks (latency, throughput, cost)
• Lead incident response, root cause analysis, and postmortems

• Partner with backend, AI, runtime, and security teams
• Guide infrastructure decisions and scaling strategy
• Mentor engineers and raise the bar on reliability and engineering standards

• Embed security into infrastructure and deployment workflows
• Design for resilience (disaster recovery, chaos testing, capacity planning)

• 8+ years of experience in DevOps, SRE, or Infrastructure Engineering
• Proven experience operating large-scale, distributed systems in production
• Deep expertise in:
• • Kubernetes & container orchestration
  • Pulumi (or similar IaC tools)
  • Cloud or hybrid environments (AWS, GCP, Azure, or on-prem)
  • Observability stacks (Prometheus, Grafana, OpenTelemetry)
• Strong experience with CI/CD, automation, and release engineering
• Proficiency in Python, Go, or Bash
• Strong systems thinking and debugging skills in high-scale environments
• Experience defining and operating with SLOs / SLAs
• Experience in startup environments
• Comfortable leveraging AI coding tools and agents to move faster

• Experience with AI/ML infrastructure or GPU workloads
• Familiarity with distributed or high-performance compute systems
• Exposure to platform engineering / internal developer platforms
• Experience scaling systems from Beta to production

• Work on cutting-edge AI infrastructure
• Build systems that power developers and enterprises
• High ownership, fast execution, real impact
• Collaborative, high-caliber team