Cloud Developer

Vanderbilt University•Nashville, TN

About The Position

The Cloud Developer performs infrastructure and development work supporting Vanderbilt’s digital scholarship, cloud-based research computing, and generative AI initiatives. Working with technologists across the Heard Libraries and other campus units, the role designs, builds, and maintains scalable cloud infrastructure that makes research data scalable and accessible. The position combines technical execution, project management, and mentorship, including serving as a “Principal Engineer” in experiential learning programs and helping students develop and deploy computational solutions. The role is part of the Digital Lab at the Jean and Alexander Heard Libraries. The Lab supports faculty- and student-driven digital projects, turns library collections into machine-readable computational assets, and develops software that leverages generative AI. A core focus is the AWS-sponsored Vanderbilt Cloud Innovation Lab, where student fellows gain hands-on software development experience. The Cloud Developer designs and maintains primarily AWS-based infrastructure, develops generative AI and machine-learning pipelines, and ensures projects use sustainable, well-documented technical stacks. The role manages assigned projects and faculty-driven R&D initiatives, coordinates technical requirements with campus partners, recruits and mentors student fellows and research assistants, and supports external grant applications by documenting staff technical expertise and infrastructure costs. It also explores and implements emerging technologies through “fail-fast” innovation.

Requirements

Undergraduate degree in computer science, cloud computing, data science, or a related technical discipline, or equivalent professional experience and industry certifications.
Two to four years of relevant experience.
Proven experience provisioning and managing cloud environments, preferably AWS, including EC2, S3, Lambda, and IAM infrastructure.
Proficiency in programming languages used for data processing and cloud back ends, such as Python or Node.js.
Familiarity with deploying generative AI models, vector databases, or orchestration frameworks, and handling distributed data storage.
Experience with version control such as Git, CI/CD pipelines, and infrastructure-as-code (IaC).
Strong interpersonal skills and ability to translate complex technical requirements for non-technical faculty or students.
Demonstrated ability to manage multiple small-to-medium digital projects simultaneously in a fast-paced, collaborative environment.

Nice To Haves

Postgraduate degree.
AWS Certified Solutions Architect, SysOps Administrator, or Developer certification.
Experience with modern web frameworks and frontend development.
Experience mentoring novice developers.

Responsibilities

Design, deploy, and maintain secure, scalable cloud infrastructure, primarily using AWS, for digital scholarship platforms and large library archives.
Implement and scale generative AI pipelines and machine-learning models for tasks such as metadata enrichment and text extraction.
Ensure faculty and institutional projects use modern, sustainable, well-documented technical stacks that integrate with university infrastructure.
Manage the full lifecycle of assigned digital projects, including timelines, deliverables, and resource allocation across partner units.
Act as an agile project manager for selected faculty-driven R&D initiatives, maintaining transparent communication and consistent progress.
Coordinate technical requirements and project scope with Research IT, ACCRE, the Data Science Institute, and other campus partners.
Recruit, interview, and hire undergraduate and graduate student fellows and research assistants.
Embed students in professional software development workflows, conduct code reviews, and provide technical mentorship.
Guide student teams through deployment challenges while balancing structured learning and software delivery.
Work with Digital Lab leadership to document staff technical expertise and infrastructure costs for external grant applications.
Explore and implement emerging technologies through “fail-fast” innovations in generative AI and research computing.