DevOps Engineer, Data & AI Platform

Responsibilities

• Build and operate infrastructure for data pipelines and AI/ML workloads.
• Develop and maintain CI/CD for application and model lifecycles, including build, train, and deploy workflows.
• Manage Infrastructure as Code with Terraform across environments.
• Support containerized workloads and orchestration with Docker and Kubernetes.
• Partner with machine learning teams and engineering to productionize models.
• Implement monitoring, logging, and tracing for data flow and model performance.
• Improve reliability, scalability, and cost efficiency of data systems.
• Enforce security and access controls for data and infrastructure.
• Reduce operational overhead through automation and tooling.

Requirements

• 3+ years of experience in DevOps, SRE, or infrastructure engineering.
• End-to-end MLOps/LLMOps expertise, including deploying and maintaining ML/AI workflows and promoting models, datasets, and code through their lifecycles.
• Strong cloud experience; AWS preferred.
• Proficiency with Terraform or similar infrastructure-as-code tools.
• Experience with Docker and Kubernetes.
• Familiarity with CI/CD and Git-based workflows.
• Experience supporting data platforms such as Airflow, Kafka, Spark, or similar technologies.
• Programming or scripting experience with Python, Bash, or similar languages.
• Experience with observability tools and practices.

Nice-to-haves

• Experience with MLOps tooling such as MLflow, SageMaker, or Kubeflow.
• Familiarity with LLM-based systems and AI observability, including token-usage tracking, prompt versioning, and evaluation loops.
• Experience with real-time or high-throughput data systems.
• Exposure to security and compliance requirements such as SOC 2 and HIPAA.
• Experience with Outerbounds, SageMaker, Metaflow, or vector databases.

Compensation and Benefits

• Base salary range: $144,300–$180,350 USD annually.
• Medical, dental, vision, life, and disability insurance.
• 401(k) plan with company match.
• Flexible Time Off, wellbeing days, paid holidays, and summer Fridays.
• Mental health resources.
• Paid parental leave and backup care.
• Tuition reimbursement.
• Employee Resource Groups (ERGs).