[Hiring] Cloud Engineer @Princeton University

Role Description

The Accelerator seeks a part-time Cloud Engineer to design, build, and operate the secure cloud infrastructure that powers large-scale academic research on the information environment. 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.

This position is classified at the Senior Engineer level, corresponding to 5–8 years of relevant experience.

• Plan and execute work independently, applying sound judgment in the evaluation, selection, and adaptation of technical approaches across infrastructure, security, and software development.
• Design and implement solutions with broad ownership — from initial architecture through deployment and ongoing operations.
• Devise new approaches to novel problems, drawing on extensive knowledge across cloud infrastructure, DevSecOps, and software engineering disciplines.
• Serve as a technical resource for the broader team, contributing to architectural decisions and engineering standards.

Responsibilities

Cloud Infrastructure

• Design, deploy, and maintain cloud infrastructure on Azure, ensuring performance, cost-effectiveness, and reliability.
• Architect and manage Databricks workspaces, including compute cluster configuration and cost optimization.
• Manage Azure networking, storage, identity, and resource governance across multiple environments.
• Implement infrastructure-as-code using Terraform and/or Bicep.
• Deploy, operate, and maintain AKS clusters running containerized workloads.
• Administer Azure Blob Storage, including lifecycle policies and redundancy configuration.
• Manage Azure networking and security, including Private Link and RBAC.
• Own Azure cost management: budget alerts, cost/cluster policies, and anomaly detection.

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.
• Build and maintain internal tooling that improves the experience of the research and operations teams.
• Contribute to frontend integrations where needed.

Data Engineering & ML Infrastructure

• Develop and support data pipelines for ingesting and transforming large-scale datasets.
• Implement and maintain infrastructure for machine learning workflows.
• Support integration with ML frameworks and tools.

Security & Compliance

• Implement and maintain security controls across all systems.
• Design and operate environments meeting IRB and data governance requirements.
• Conduct regular security reviews and vulnerability assessments.
• Implement audit logging and data handling procedures for sensitive research data.

Observability & Operations

• Operate, patch, and upgrade the self-hosted observability stack.
• Own incident response, root cause analysis, and operational reliability for production systems.
• Develop and maintain runbooks and architecture documentation.

Qualifications

• 5–8 years of experience in cloud engineering, DevOps, or a software engineering role.
• Bachelor's degree in Computer Science, Engineering, or a related field or equivalent work experience.
• Strong proficiency in Python; experience with at least one additional language.
• Deep hands-on experience with Azure cloud services.
• Proficiency with Terraform; Bicep familiarity a plus.
• Experience designing and implementing CI/CD pipelines.
• Production experience with Kubernetes / AKS.
• Solid Docker and container image management skills.
• Azure networking and security fundamentals.
• Azure cost management and FinOps awareness.
• Experience with Databricks or equivalent large-scale data processing platforms.
• Solid understanding of data security principles and compliance frameworks.
• Experience operating a self-hosted observability stack.
• Ability to work independently on complex problems.
• Strong written communication skills.

Requirements

• A combination of relevant work experience and education equivalent to 5–8 years of hands-on cloud engineering or software engineering experience.
• A bachelor's degree in Computer Science, Engineering, or a related field is preferred but not required.

Benefits

• Part-time, benefits-eligible, 12-month term position.
• Prorated base salary range is approximately $71,723/year - $77,240/year.
• Remote work arrangement may be considered.