Cloud Engineer

## Overview The Accelerator seeks a Cloud Engineer to design, build, and operate the secure cloud infrastructure that powers large-scale academic research on the information environment. Working as part of a small, high-trust cross-functional team, this individual will contribute across the full stack — from infrastructure and DevOps to backend services and data pipelines — and will have meaningful ownership over the technical systems that enable researchers at Princeton and across a global consortium to do their work. This is a role for a senior, self-directing engineer who is equally comfortable designing architecture and writing code, and who takes satisfaction in building systems that are reliable, secure, and well-understood by the people who depend on them. The right candidate brings deep cloud expertise alongside strong software engineering fundamentals — someone who can own infrastructure end to end and contribute meaningfully to application development. ## Responsibilities **Cloud Infrastructure** - Design, deploy, and maintain cloud infrastructure on Azure, with responsibility for performance, cost-effectiveness, and reliability across research and production environments. - Architect and manage Databricks workspaces, including compute cluster configuration, access controls, and cost optimization for large-scale data processing workflows. - Manage Azure networking, storage, identity (Azure AD / Entra ID), and resource governance across multiple environments. - Implement infrastructure-as-code using Terraform and/or Bicep; maintain version-controlled, reproducible infrastructure definitions including modules, remote state management, and PR-based workflow. - Deploy, operate, and maintain AKS clusters running containerized workloads — including containerized data crawlers — managing deploys, scaling, health monitoring, patching, and upgrades. - Administer Azure Blob Storage, including lifecycle policies, redundancy configuration, and access tier management. - Manage Azure networking and security, including Private Link, network rules, RBAC, and secrets hygiene across environments. - Own Azure cost management: budget alerts, cost/cluster policies, anomaly detection and response, and FinOps practices to keep infrastructure spend predictable and efficient. **Software Development & DevOps** - Design, build, and maintain backend services, APIs, and data pipelines using Python and/or TypeScript/Node.js. - Develop and maintain CI/CD pipelines using GitHub Actions, ensuring reliable and automated delivery of infrastructure and application changes. - Build and maintain internal tooling that improves the experience and efficiency of the research and operations teams. - Contribute to frontend integrations where needed; comfortable working across the stack on a small team. **Data Engineering & ML Infrastructure** - Develop and support data pipelines for ingesting, transforming, and serving large-scale behavioral and social media datasets to researchers. - Implement and maintain infrastructure for machine learning workflows, including model serving, experiment tracking, and compute resource management. - Support integration with ML frameworks and tools (e.g., MLflow, Hugging Face, or equivalent) within the managed environment. **Security & Compliance** - Implement and maintain security controls across all systems, including encryption at rest and in transit, identity and access management, network segmentation, and secrets management. - Design and operate environments meeting IRB, data governance, and institutional compliance requirements; ensure adherence to standards equivalent to SOC 2, HIPAA, or ISO 27001 as applicable. - Conduct regular security reviews, vulnerability assessments, and penetration test coordination; manage remediation tracking. - Implement audit logging, access controls, and data handling procedures for sensitive research data in compliance with IRB protocols and data use agreements. **Observability & Operatio…