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webAI is building distributed AI infrastructure for personalized, privacy-preserving AI deployment at the edge. The company is developing an end-to-end platform that keeps enterprise data and IP private while enabling large-scale AI models to run on standard consumer hardware.
As a Senior DevOps Engineer, you will design, build, and scale secure infrastructure supporting AI workloads across cloud and edge environments. This is a high-impact individual contributor role focused on infrastructure architecture, platform reliability, and security best practices.
Key responsibilities include:
- 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
- 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
- Mentor junior and mid-level engineers on DevOps best practices and infrastructure design
You will work closely with engineering teams to implement scalable, automated infrastructure solutions that enable the AI platform to operate efficiently across diverse deployment scenarios. This role requires strong technical depth, production experience, and the ability to translate complex requirements into resilient infrastructure systems.
QUALIFICATIONS:
- 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.)
