DevOps Engineer (Data & AI Platform)
Core
Building reliable infrastructure for data pipelines and ML systems, standardizing deployment patterns, and ensuring performance, observability, and cost efficiency across compute-intensive workloads.
Role type
DevOps Engineer (Data & AI Platform)
Builds
Production-ready data pipelines and AI/ML systems
Domain
Cloud infrastructure, Data Engineering, Machine Learning Operations
Deliverable
production ML models
Required skills
Infrastructure as Code (Terraform), Container orchestration (Kubernetes), CI/CD pipelines, Cloud platforms (AWS), Data platform tools (Airflow, Kafka, Spark), Scripting (Python, Bash), Observability tooling
Preferred skills
MLOps tooling (MLflow, SageMaker, Kubeflow), LLM system management, Real-time data systems, Security compliance (SOC 2, HIPAA), Vector databases
Technologies
Terraform, Docker, Kubernetes, AWS, Airflow, Kafka, Spark, Python, Bash, MLflow, SageMaker, Kubeflow
Responsibilities
Build and operate infrastructure for data pipelines and AI/ML workloads; Develop and maintain CI/CD for application and model lifecycle; Manage Infrastructure as Code across environments; Support containerized workloads and orchestration; Partner with Machine Learning teams 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
Seniority
Mid-level, hands-on IC
