DevOps Engineer - Senior Vice President

Responsibilities

• Design, build, and operate MLOps pipelines supporting the full ML lifecycle (training, validation, deployment, monitoring).
• Enable production workloads for AI/ML and Generative AI systems, including LLM-based services.
• Develop and maintain CI/CD pipelines for AI/ML services and supporting infrastructure.
• Build and manage cloud-native infrastructure on AWS, with heavy use of Kubernetes and containerized workloads.
• Automate infrastructure provisioning and configuration using Infrastructure as Code (Terraform).
• Implement model versioning, experiment tracking, and artifact management across environments.
• Ensure reliability, scalability, observability, and cost efficiency of AI platforms.
• Partner with AI/ML engineers to operationalize models and standardize deployment patterns.
• Implement monitoring and alerting for system health, model performance, and drift.
• Enforce security, compliance, and governance requirements for AI workloads.
• Participate in incident response, root cause analysis, and continuous improvement initiatives.

Qualifications

• 15+ years of experience in DevOps, SRE, or Platform Engineering, with AWS as a primary cloud.
• Experience supporting machine learning systems in production, including deployment and monitoring concerns.
• Hands-on experience with machine learning platforms, particularly AWS SageMaker (required).
• Strong hands-on experience with Kubernetes, containerized workloads, and cloud networking.
• Proven experience building and operating CI/CD pipelines (e.g., GitLab CI, ArgoCD).
• Strong proficiency with Terraform and scripting/programming in Python or similar languages.
• Solid Linux, systems, and troubleshooting fundamentals.
• Excellent communication skills and ability to work across teams.
• Direct experience with MLOps platforms and tooling (model registries, experiment tracking, feature stores).
• Exposure to Generative AI / LLM workloads in production environments.
• Familiarity with data stores commonly used in ML systems (e.g., Postgres, DynamoDB, object storage).
• Experience operating in regulated or fintech environments.
• Background in cost optimization for compute-intensive workloads.
• Strong written and verbal communication skills.

Pay

The base salary range for this role is $180,000 to $230,000 depending on experience.

Schedule

Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.