# DevOps Engineer at Fundamental

> Remote · Europe · Unspecified · DevOps / SRE / Infra · open. Source: https://alderhq.app/jobs/ashby%3AFundamental%3A3f7ce69f-14c2-403d-9cfe-9b463c923dd5 (read 2026-11-14).

## Facts (observed)

- Company: [Fundamental](https://alderhq.app/companies/fundamental)
- Location text: Europe
- Where it can be done from (inferred): Remote · Europe (evidence: "Location: Europe")
- Posted: 2025-12-02 (347 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-09
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/Fundamental/3f7ce69f-14c2-403d-9cfe-9b463c923dd5
- Skills listed (inferred): Python, FastAPI, AWS, GCP, Kubernetes, Terraform, Snowflake, Distributed systems

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### About Fundamental

Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict.

At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.

### Key responsibilities

Design and implement cloud infrastructure from the ground up

Build and maintain Kubernetes clusters optimized for GPU workloads and ML applications, as well as Production SaaS hosting

Implement GitOps practices using ArgoCD for continuous deployment

Develop infrastructure as code using Terraform

Create and maintain CI/CD pipelines for infrastructure and application deployment

Implement monitoring and observability solutions for distributed systems

Automate infrastructure management with Python and Bash

Collaborate with ML engineers to optimize infrastructure for model training and serving

Implement and maintain cost optimization strategies (FinOps) for cloud resources

Monitor and optimize cloud spending, especially for GPU-intensive workloads

### Must have

5+ years of experience in cloud infrastructure and DevOps

3+ years of experience with Python

Strong experience with AWS and GCP cloud platforms

Deep expertise in Kubernetes, including multi-cluster management, GPU workload optimization, resource scheduling and autoscaling, and network policies and security

Experience with GitOps tools (ArgoCD preferred)

Extensive experience with cloud networking, including VPC design, load balancer configuration, network security and segmentation, and cross-cloud networking solutions

Strong CI/CD expertise, preferably with GitHub Actions

Proficiency in infrastructure as code (Terraform)

Experience with monitoring and observability tools

Experience with FinOps practices and cloud cost optimization

### Nice to have

Experience with ML workflow tooling (MLflow, Kubeflow, or similar)

Experience with FastAPI and Backend applications

Familiarity with data platforms like Databricks or Snowflake

Exposure to SRE practices or cloud security certifications

Hands-on experience with Prometheus, Grafana, or Datadog

### Benefits

Competitive compensation with salary and equity

Comprehensive health coverage for you and your dependents

Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys

Relocation support for employees moving to join the team in one of our office locations

A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3AFundamental%3A3f7ce69f-14c2-403d-9cfe-9b463c923dd5 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.
