Senior DevOps Engineer

webAI; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity options

Parental leave

401(k) plan

Health coverage

Learning stipend

Remote-first with flexible time off

Job summary

webAI seeks a Senior DevOps Engineer to design, build, and scale secure infrastructure supporting AI workloads across cloud, hybrid, and edge environments. You will drive architecture, platform reliability, and security across the org.

You will work closely with engineering teams to implement scalable, automated infrastructure solutions enabling the AI platform to operate efficiently—from public cloud to edge deployments.

Qualifications

• 5–8+ years of DevOps, SRE, or infrastructure engineering experience.
• Hands-on with multi-cloud (AWS/Azure/GCP) and edge deployments.
• Proficient in IaC (Terraform, Pulumi, Ansible) and GitOps.
• Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD).
• Strong automation, security, and cost-optimization practices.

Responsibilities

• Design, build, and scale secure infra for AI workloads.
• Implement scalable, automated infrastructure across cloud, hybrid, and edge.
• Deploy and operate Kubernetes clusters for AI/ML workloads.
• Develop secure CI/CD pipelines with integrated security controls.
• Support MLOps infrastructure initiatives including model deployment automation.
• Implement observability and monitoring.
• Enforce IAM, encryption, network segmentation, and compliance automation.
• Mentor junior engineers on DevOps practices.

Skills

DevOps

SRE

Kubernetes

Docker

CI/CD

Python

Cloud platforms

Security practices

Tools

Terraform

Pulumi

Ansible

GitHub Actions

GitLab CI

Jenkins

ArgoCD

Istio

Linkerd

Job description

• We are seeking a Senior DevOps Engineer to design, build, and scale secure infrastructure supporting AI workloads across cloud and edge environments. This is a high-impact individual contributor role where you will help drive infrastructure architecture, platform reliability, and security best practices across the organization
• You will work closely with engineering teams to implement scalable, automated infrastructure solutions that enable our AI platform to operate efficiently across diverse deployment scenarios—from public cloud to hybrid and edge environments
• Design and implement secure, scalable infrastructure across multi-cloud (AWS, Azure, GCP), hybrid, and edge environments
• Build and maintain Infrastructure as Code (Terraform, Pulumi, Ansible) using GitOps workflows and automated validation
• Deploy and operate Kubernetes clusters optimized for AI/ML workloads, including GPU scheduling and container security best practices
• Develop secure CI/CD pipelines with integrated security controls (SAST, DAST, vulnerability scanning, secrets management)
• Support MLOps infrastructure initiatives including model deployment automation, versioning, and lifecycle management
• Implement observability and monitoring frameworks using tools such as Prometheus, Grafana, ELK, or Datadog
• Enforce security best practices including IAM, encryption, network segmentation, and compliance automation
• Participate in incident response, reliability improvements, postmortems, and disaster recovery planning
• Develop reusable infrastructure modules and documentation (runbooks, architecture docs, standards)
• Mentor junior and mid-level engineers on DevOps best practices and infrastructure design

Benefits

• Grow with us: Equity options so you share in our growth. Build your future as we build ours.
• Family first: Parental leave and fertility support for every stage of life. Your family matters here.
• Plan your future: A 401(k) to help you save and invest. Secure what’s ahead with confidence.
• Stay well: Comprehensive health coverage for body and mind. Because balance fuels great work.
• Keep learning: A stipend to explore, study, and sharpen your skills. Growth never stops.
• Work anywhere: Remote-first with flexible time off to recharge. Find balance wherever you are.

Requirements

• strong technical depth, production experience, and the ability to translate complex requirements into resilient infrastructure systems
• 5–8+ years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering supporting production systems
• Strong understanding of cloud security best practices and access management
• Strong expertise with Docker, Kubernetes, and cloud-native architectures
• Experience working with AWS, Azure, or GCP including compute, networking, and managed services
• 3–5+ years of hands‑on experience implementing Infrastructure as Code (Terraform, Pulumi, Ansible)
• Proven experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
• Experience implementing monitoring and observability in production environments
• Programming experience in Python (preferred), Go, or Bash for automation
• Strong communication skills and ability to collaborate cross‑functionally
• Exposure to multi‑cloud or hybrid cloud environments
• Experience supporting AI/ML or MLOps workflows
• Experience with edge computing or distributed systems
• Familiarity with service mesh technologies (Istio, Linkerd)
• Understanding of cost optimization and cloud efficiency practices
• Relevant certifications (CKA, AWS Solutions Architect, Terraform Associate, etc.)