Senior DevOps Engineer

WebAI, Inc.
Austin, TX, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Kubernetes Security Artificial Intelligence Amazon Web Services Microsoft Azure Bash Shell Cloud Computing Cloud Computing Security Cloud Engineering Computer Programming DevOps Disaster Recovery Distributed Systems
+31 more
Github Monitoring of Systems Identity and Access Management Python (Programming Language) Key Management Network Segmentation Octopus Deploy Reliability Engineering Ansible Prometheus Runbook Management of Software Versions Datadog Pulumi Google Cloud Istio Grafana Multi-Cloud HybridCloud AI Platforms Gitlab-ci Kubernetes Linkerd (Service Mesh) Machine Learning Operations Multiaccess Edge Computing Terraform Docker Jenkins Static Application Security Testing Vulnerability Analysis Dynamic Application Security Testing

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. This role requires strong technical depth, production experience, and the ability to translate complex requirements into resilient infrastructure systems.

This position will be hybrid in Austin Texas or Grand Rapids Michigan., * 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, * Ownership - Taking full responsibility for one’s actions and decisions, demonstrating commitment to the success of our clients.* * * * *
  • Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement.
  • Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others.

Requirements

DevOps, Embedded Systems, Sales Closing Skills, Artificial Intelligence (AI), Intellectual Property (IP), Best Practices, Cloud Computing, DevOps, Public Cloud, Team Player, * 5-8+ years of experience in DevOps, Site Reliability Engineering, or Infrastructure Engineering supporting production systems

  • Strong expertise with Docker, Kubernetes, and cloud-native architectures
  • 3-5+ years of hands-on experience implementing Infrastructure as Code (Terraform, Pulumi, Ansible)
  • Experience working with AWS, Azure, or GCP including compute, networking, and managed services
  • Proven experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
  • Programming experience in Python (preferred), Go, or Bash for automation
  • Experience implementing monitoring and observability in production environments
  • Strong understanding of cloud security best practices and access management
  • Strong communication skills and ability to collaborate cross-functionally

Preferred Skills:

  • Exposure to multi-cloud or hybrid cloud environments
  • Experience supporting AI/ML or MLOps workflows
  • Familiarity with service mesh technologies (Istio, Linkerd)
  • Experience with edge computing or distributed systems
  • Understanding of cost optimization and cloud efficiency practices
  • Relevant certifications (CKA, AWS Solutions Architect, Terraform Associate, etc.)

Benefits & conditions

We strive to provide competitive benefits to all employees. The benefits listed in this posting generally apply to U.S.-based employees. For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.

  • Competitive salary and performance-based incentives
  • Comprehensive health, dental, and vision benefits package
  • Including a high-deductible HSA option with $200/month company contribution
  • 401k match (US-based only)
  • Equity options
  • Flexible PTO Policy
  • Parental leave for eligible employees
  • Continuing education support
  • Basic, company-paid life insurance
  • Supplemental life insurance
  • Company-paid short and long term disability
  • Free parking for in-office employees

About the company

webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company’s valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the

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