Devops Engineer

This is a remote position.

About the role

A well-funded, seed-stage industrial-AI company is looking for an experienced, hands-on DevOps engineer who

has already built and managed infrastructure in an early-stage startup or taken a system from zero. You will own

the cloud infrastructure and set the standards for security, monitoring and incident response. You will also work as

a core partner on the infrastructure that serves the company’s main ML/AI models. We need a versatile generalist

who can work independently with little oversight and take on a wide range of responsibilities.

What you will own

• Infrastructure: Design, deploy and run scalable, highly available infrastructure across multiple cloud

environments using Infrastructure as Code (for example Terraform or CloudFormation).

• CI/CD: Build, run and improve the CI/CD pipelines used across the whole company.

• Observability: Set up and operate monitoring, logging and alerting (for example Prometheus, Grafana or the

ELK stack) so services stay healthy and perform well.

• Security: Define and enforce security practice across infrastructure and applications, covering secrets

management, network segmentation and vulnerability patching.

• Cloud cost: Look for savings in cloud spend on your own initiative and put them in place without hurting

performance or reliability.

• Engineering support: Work alongside engineers to make development workflows smoother, resolve

production issues and support their infrastructure needs.

What we are looking for

• At least 5 years as a DevOps engineer, Site Reliability Engineer (SRE) or in a comparable role.

• Proven experience in a seed-stage startup or a ground-up build, and an understanding of what that means:

limited resources, quick changes of direction and a hands-on, do-everything approach.

• Solid working knowledge of Docker and Kubernetes (EKS, GKE or AKS).

• Expert-level skill with Terraform or a comparable Infrastructure as Code tool.

• Experience building and maintaining CI/CD pipelines (for example GitLab CI, GitHub Actions or Jenkins).

• Hands-on database administration experience (for example PostgreSQL, MongoDB or Redis).

Nice to have

• MLOps experience, including production serving infrastructure for machine learning models.

• Security certifications, or deep experience with cloud security frameworks.

• Experience with on-prem deployments and observability.

• Experience building and deploying ML models on real-time time-series data, such as sensor or IoT streams.

To apply: send your resume and a short example of infrastructure you built or ran yourself, with your role and the

outcome. Sanitized descriptions are fine.

Posted by MantriAI, search partner for the company. Shortlisted applications may hear from us within 48 hours.