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Salary
≈ $25k – $58k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Feb 20, 2026. FlexAI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
FlexAI is an artificial intelligence infrastructure company headquartered in Paris, France, and founded in 2023 by former Apple, Intel, and NVIDIA engineers. The company offers workload as a service, abstracting away the specific accelerator so training and inference jobs can run across mixed GPU and alternative silicon without rewriting code. It targets European AI teams that want compute portability and sovereignty rather than lock-in to a single cloud or chip vendor.

About FlexAI

Build and Deploy AI the right way, anywhere.

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.

Founded byBrijesh Tripathi, who bring experience from Nvidia, Apple, Tesla, Intel and Zoox, FlexAI is notjustbuilding a product - we’re shaping the future of AI. Our teams are strategically distributed across Silicon Valley and Bengaluru, united by a shared mission: to deliver more compute with less complexity.

If you're passionate about shaping the future of artificial intelligence, driving innovation, and contributing to a sustainable and inclusive AI ecosystem,FlexAI is the place for you !

Role Overview

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.

What You’ll Do

Own Reliability & Architecture:

  • 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)

Build Infrastructure at Scale:

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

CI/CD & Automation:

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

Observability & Performance:

  • 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

Leadership & Collaboration:

  • 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

Security & Resilience:

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

What You'll Need to Be Successful

  • 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

Nice to Have

  • 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

Why FlexAI

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