Senior DevOps Engineer (AI)

TL;DR

Senior DevOps Engineer (AI): Building and maintaining scalable infrastructure and CI/CD pipelines for generative AI applications with an accent on MLOps, Kubernetes orchestration, and cloud-native automation. Focus on operationalizing machine learning models, ensuring high availability, and optimizing infrastructure performance for production-grade AI systems.

Location: Must be based in the United States

Compensation: $140,000–$220,000

Company

A global analytics software leader powering decision-making for businesses in over 100 countries.

What you will do

• Design, build, and maintain scalable infrastructure and data pipelines using Terraform and Kubernetes.
• Operationalize machine learning models by building automated training, validation, and deployment pipelines.
• Collaborate with SRE teams to ensure high availability, security, and observability of ML infrastructure.
• Automate infrastructure provisioning using AWS cloud-native services and IaC best practices.
• Manage EKS/ECS environments while optimizing performance and cloud costs.
• Support experimentation and transition of AI prototypes into robust production systems.

Requirements

• 7+ years of experience in DataOps or MLOps with a minimum of 2 years in ML model operationalization.
• Must be authorized to work in the United States as the role is restricted to US-based candidates.
• Proficiency in AWS services (EC2, S3, IAM, EKS, ECS).
• Strong scripting skills in Python and experience with IaC tools like Terraform.
• Experience with GitOps practices and CI/CD tools such as GitHub Actions or Argo Workflows.
• Solid understanding of cloud security, identity access management, and monitoring tools like Prometheus or Datadog.

Nice to have

• Experience with data governance, lineage, and metadata management.
• Familiarity with OpenTelemetry for advanced observability.

Culture & Benefits

• Inclusive team environment focused on diversity and equal employment opportunities.
• Professional development and learning opportunities within a leading big data analytics organization.
• Competitive compensation and benefits programs tailored for long-term career growth.
• Emphasis on work-life balance and social engagement through employee resource groups.