Responsibilities

• Design, architect, and deploy cloud-native applications using modern patterns (microservices, containers, Kubernetes, serverless).
• Build and manage cloud infrastructure using Infrastructure as Code (Terraform, CloudFormation).
• Configure and optimize infrastructure for parallel processing of large-scale AI and data workloads.
• Instrument observability and monitoring for QuadSci products, including data pipelines, AI services, and action workflows (e.g. Azure Monitor, Google Cloud Operations Suite,Grafana, Loki, OpenTelemetry).
• Partner with customer DevOps and SRE teams to design and implement CI/CD pipelines and deployment strategies.
• Collaborate with Data/ML Engineers to provision and optimize infrastructure for AI workloads leveraging Azure Machine Learning, Vertex AI, and managed compute services.
• Work with Full Stack Engineers to design backend cloud services and deployment architectures.
• Act as a trusted cloud advisor across 1–5 customer environments.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related field.
• 3+ years of experience in cloud architecture, platform engineering, or DevOps.
• Strong experience with cloud-native application design, containers, and Kubernetes.
• Proficiency with Infrastructure as Code tools (Terraform, CloudFormation).
• Hands-on experience designing and maintaining CI/CD pipelines.
• Experience implementing cloud security best practices (IAM, encryption, vulnerability scanning).
• Experience with monitoring, observability, and performance optimization.
• Familiarity with observability tooling (e.g., Grafana, Loki, Elasticsearch).
• Experience deploying applications via containers and modern CI/CD platforms (GitHub, GitLab, Bitbucket).