About QuadSci.ai QuadSci is an AI product company that uses fine-tuned AI on customer data and telemetry to predict churn, contraction, and growth up to 12 months ahead for software companies. We bridge the gap between AI progress and great customer experiences, helping software companies prioritize customers to boost performance. QuadSci enables GTM leaders (Sales, Customer Success, Services, etc.) to scientifically manage the customer lifecycle, GTM performance, and ARR predictability, significantly aiding the \"Rule of 40.\" About the Role As a Cloud Native Engineer at QuadSci, you will design, deploy, and operate the cloud infrastructure that powers our AI products across multiple customer environments. You are both a platform engineer and a trusted customer-facing cloud architect, responsible for ensuring QuadSci’s products are scalable, secure, observable, and production-ready. You will work closely with Data/ML Engineers, Full Stack Engineers, and customer DevOps/SRE teams to deliver reliable AI-driven systems that process large volumes of data and operate at scale. What You’ll Do 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. Basic Qualifications (Must Have) 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). Advanced Qualifications (Nice to Have) Master’s degree in a related field. Experience with serverless architectures and frameworks. Experience supporting or building MLOps pipelines. Strong understanding of networking concepts (VPCs, load balancing, service meshes such as Istio or Linkerd). Familiarity with Python-based APIs. Cloud certifications (AWS, GCP, Azure, Snowflake). Experience with Azure-native services (AKS, Azure Container Registry, Azure Data Factory, Azure Synapse Analytics, Azure Databricks).  Experience with GCP-native services (GKE, Artifact Registry, Cloud Composer, BigQuery, Dataflow, Dataproc). Experience with OpenTelemetry and distributed tracing. At QuadSci, we believe equal opportunity fuels innovation and strengthens our culture. We actively welcome candidates from all backgrounds and are committed to creating an environment where everyone can thrive on the merits of their efforts and outcomes. QuadSci is an equal opportunity/affirmative action employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state, or local law, ordinance, or regulation.