DevOps Engineer, Data & AI Platform
The DevOps Engineer will build and operate reliable infrastructure, deployment workflows, and observability for data pipelines and AI/ML systems. The role requires at least three years of DevOps, SRE, or infrastructure experience plus strong cloud, Terraform, containerization, and MLOps expertise.
About the job
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).
Skills
AWS, Terraform, Docker, Kubernetes, CI/CD, Git, Airflow, Kafka, Spark, Python, Bash, MLflow, SageMaker, Kubeflow, MLOps
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