Cloud Native Engineer

QuadSci is a New York-based AI startup that helps B2B SaaS companies predict customer churn, identify expansion opportunities, and optimize revenue operations. Its platform analyzes billions of product telemetry signals, CRM data, and customer interactions to generate predictive insights that enable GTM, Customer Success, Product, and Revenue teams to take proactive action.

• 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.

• 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).