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Senior DevOps Engineer

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Summary

Senior DevOps/SRE engineer who deploys, operates, and scales Kubernetes-based microservices and GPU-backed ML inference (Triton, vLLM) across AWS, GCP, and on-prem, using Terraform, Ansible, Python, GitHub/GitLab CI/CD, and Grafana/Prometheus observability. The team builds voice-first AI products (speech, NLP, generative AI) with on-prem deployment.

We are looking to strengthen our team for a DevOps/SRE Engineer!

Requirements:

  • Minimum 5 years of experience in a DevOps and/or Site Reliability Engineering role
  • Strong hands-on experience with Linux system administration
  • Extensive experience deploying, operating, and scaling Kubernetes in both cloud and bare-metal environments
  • Deep expertise and practical experience with at least one major cloud provider (preferably Google Cloud Platform)
  • Experience with ML inference on GPU/CPU is a strong plus
  • Proven experience implementing SRE practices and building observability stacks using Grafana, Prometheus, and Loki
  • Strong adherence to GitOps, Infrastructure as Code (IaC), and CI/CD principles
  • Advanced expertise in Terraform, Ansible, and Python
  • Comfortable working in high-uncertainty environments: we are building a new product, requirements evolve quickly, and the ability to rapidly learn new technologies and patterns is essential
  • Proactive mindset: ability to look beyond DevOps tasks and actively debug and understand the product
  • Strategic thinking: ability to choose technologies and architectural approaches based on long‑term goals rather than short‑term compromises

Responsibilities:

  • Deploy, operate, and evolve a microservices‑based platform running in Kubernetes clusters across AWS, GCP, and on‑prem (Rancher)
  • Operate and support GPU‑based ML inference services (Triton Inference Server, vLLM) deployed on RunPod, Scaleway, and Nebius
  • Build and maintain Docker images for all microservices and ensure a stable service lifecycle
  • Maintain and scale development and production Kubernetes clusters, actively participate in deployment debugging, incident investigation, and performance troubleshooting
  • Develop, maintain, and evolve custom Helm charts for each service
  • Design and operate CI/CD pipelines using GitHub (code and pipelines) and GitLab for on‑prem customer deployments
  • Ensure platform compliance with SOC 2 requirements and actively contribute to improving security and compliance processes
  • Manage cluster access via NetBird VPN, implementing role‑based access control using group policies
  • Deploy and manage infrastructure using IaC practices with Terraform and Ansible
  • Develop and continuously improve observability systems:Grafana & Prometheus for metricsELK stack for centralized log storage and analysis
  • Continuously optimize infrastructure in the areas of IaC, IAM, Observability, and CI/CD

Work with a technology stack, including:

  • Python
  • Kubernetes
  • Linux
  • Docker
  • GitHub CI/CD
  • PostgreSQL
  • ClickHouse
  • Kafka
  • Superset
  • Terraform
  • Ansible

What we offer:

  • The team has built award‑winning AI products for tech corporations — devices, voice assistants, products that are actually in the world
  • Cutting‑edge tech stack: Speech Technologies, NLP, Generative AI (LLMs, diffusion models), voice‑first agentic architecture with privacy‑first and on‑premises deployment
  • High engineering bar and real ownership — the team cares about what actually works in production, not what looks good in a demo, and you'll see the impact of your work directly
  • Fast career progression — a senior‑heavy team and a high volume of real problems means you grow faster than you would anywhere else
  • Startup pace with enterprise stability — real clients, real revenue, no bureaucracy
  • Fully remote21 vacation days + public holidays + 5 sick daysPrivate English lessons via Preply

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