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Open nowPosted 262 days ago

DevOps Team Lead

Fundamental24 open roles

Where
Europe
Work mode
Remote
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Your applicationOpen nowDevOps Team LeadFundamental · Europe
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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. Fundamental postings stay open a median of 35 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 262 days ago

Fundamental median: 35 days open

The posting

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

- Lead and mentor a team of DevOps engineers, fostering technical growth and collaboration

- Define and drive the infrastructure roadmap aligned with company objectives

- Architect and oversee cloud infrastructure design and implementation

- Establish best practices, standards, and processes for infrastructure development and operations

- Partner with Engineering, Research, and FDE to align infrastructure capabilities with business needs

- Drive the evolution of Kubernetes clusters optimized for GPU workloads, Production SaaS hosting and and varied enterprise deployment models

- Champion GitOps practices using ArgoCD for continuous deployment

- Establish infrastructure as code standards using Terraform

- Define monitoring and observability strategy for distributed systems

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

- Own infrastructure reliability, performance, and security posture

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

MUST HAVE

- 7+ years of experience in cloud infrastructure and DevOps, with 5+ years in a technical leadership role

- Proven track record of building and leading high-performing infrastructure teams

- Strong experience with AWS, GCP and Azure

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

- 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 Terraform

- Proficiency with GitOps tools (ArgoCD preferred)

- 3+ years of experience with Python

- Experience with monitoring and observability tools

- Experience with FinOps practices and cloud cost optimization

- Excellent communication skills with ability to translate technical concepts for diverse audiences

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

- SRE practices experience or cloud security certifications

- Hands-on experience with Prometheus, Grafana, or Datadog

- Experience scaling infrastructure for AI/ML startups

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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