DevOps Engineer
Join Fundamental as a DevOps Engineer to tackle technical challenges in AI infrastructure for enterprise decision-making.
Posted by employer 11 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 13 hours ago
Skills & Technologies
AI in the day-to-day
Fundamental has developed NEXUS, an AI model that transforms enterprise decision-making.
Requirements
- Experience
- 5+ years
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In this role, the DevOps Engineer at Fundamental is responsible for designing and implementing cloud infrastructure, focusing on optimizing Kubernetes clusters for machine learning applications. Key skills include extensive experience with AWS and GCP, proficiency in Python, and a strong grasp of GitOps practices, particularly with ArgoCD. This position is ideal for seasoned professionals with over five years in cloud infrastructure and DevOps, who are eager to tackle complex technical challenges in a pioneering AI company.
Joblaze insights
- Listed about a month ago — first seen on Joblaze September 3, 2026. Last confirmed on Fundamental's careers page October 31, 2026.
- Kubernetes appears in 59% of 402 comparable senior devops/sre roles; Argo CD appears in 3.2% of 402 comparable senior devops/sre roles.
Quick facts
- How much experience is required?
- At least 5 years of relevant experience for this DevOps Engineer role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, ArgoCD, CI/CD, Datadog, FinOps, GCP.
- What seniority level is this role?
- Fundamental targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this DevOps Engineer role at Fundamental.
From the original posting
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
Standard company text repeated across Fundamental's postings is omitted here.