Staff AI Infrastructure Engineer
About The Position
We’re seeking a Staff AI Infrastructure Engineer with deep expertise in building, automating, and managing AI infrastructure at scale. You will be instrumental in designing and maintaining the systems essential for serving and deploying AI models efficiently and securely across diverse cloud environments. As a Staff AI Infrastructure Engineer, you’ll join our globally distributed team to: Architect, build, and maintain scalable infrastructure to host and serve AI products and models reliably. Automate infrastructure deployment and management using Helm, ArgoCD and Terraform. Manage and optimize Kubernetes clusters to support high-performance AI workloads. Implement and manage CI/CD pipelines utilizing GitHub Actions and Jenkins. Ensure infrastructure compliance with security standards including FedRAMP and related guidelines. Collaborate closely with AI engineering, product teams, and DevOps to meet infrastructure requirements. Monitor infrastructure health and performance, implementing optimizations proactively. Drive infrastructure best practices and mentor team members to foster technical excellence.
Requirements
- A degree in Computer Science, Information Technology, or related field, or equivalent practical experience.
- 7+ years of experience managing scalable, secure, and resilient infrastructure for AI and machine learning applications.
- Deep proficiency with infrastructure-as-code tools like Helm, Terraform and ArgoCD.
- Extensive hands-on experience with Kubernetes for deploying containerized workloads.
- Demonstrated experience with major cloud platforms (AWS, GCP, Azure), specifically with services related to AI model hosting (e.g., Azure OpenAI).
- Experience implementing and managing CI/CD pipelines (GitHub Actions, Jenkins).
- Familiarity with compliance frameworks, particularly FedRAMP, and security best practices.
- Strong scripting and automation skills using Python, Bash, or similar languages.
- Excellent problem-solving skills, creativity, and self-driven motivation.
Nice To Haves
- Previous experience as a Site Reliability Engineer (SRE), particularly in AI or ML contexts.
- Monitoring and logging tools (Prometheus, Grafana, Datadog, Jaeger).
- Networking concepts and security best practices within cloud infrastructure.
- Professional certifications in Kubernetes or cloud platforms (AWS, Azure, GCP).
Responsibilities
- Architect, build, and maintain scalable infrastructure to host and serve AI products and models reliably.
- Automate infrastructure deployment and management using Helm, ArgoCD and Terraform.
- Manage and optimize Kubernetes clusters to support high-performance AI workloads.
- Implement and manage CI/CD pipelines utilizing GitHub Actions and Jenkins.
- Ensure infrastructure compliance with security standards including FedRAMP and related guidelines.
- Collaborate closely with AI engineering, product teams, and DevOps to meet infrastructure requirements.
- Monitor infrastructure health and performance, implementing optimizations proactively.
- Drive infrastructure best practices and mentor team members to foster technical excellence.
Benefits
- Medical
- Vision
- Dental
- 401(k)
- Commuter
- Health and Dependent FSA
- Unlimited PTO
- Industry-leading gender-neutral parental leave
- Paid Company Holidays
- Paid Sick Time
- Employee stock purchase program
- Disability and life insurance
- Employee assistance program
- Gym membership reimbursement
- Cell phone reimbursement
- Numerous company-sponsored events, including regular happy hours and team-building events
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
