DevOps Engineer, Generative AI Applications, HBS FoundryBOSTON TRUST WALDEN COMPANY • United States
DevOps Engineer, Generative AI Applications, HBS Foundry
BOSTON TRUST WALDEN COMPANY
- United States
- United States
About
001883SR
School/Unit:
Harvard Business School
Department:
HBS Foundry
Job Function:
Technical
Location:
Boston
Job Type:
Full-time
Salary Grade:
059
FLSA Status:
Exempt
Union:
00 - Non Union, Exempt or Temporary
Term Appointment:
Yes
Company Description By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.
Why Join HBS Foundry? HBS Foundry is a new initiative at Harvard Business School that helps founders build, fund, and launch their ventures through an AI-driven digital learning platform. We’re a small, collaborative team within one of the world’s most respected institutions—combining the energy of a startup with the mission and reach of Harvard. Foundry brings together educators, engineers, and creative thinkers who are passionate about innovation, learning, and impact. Together, we’re developing tools and experiences that empower founders to grow their ventures and their confidence. It’s an exciting, fast-moving environment where new ideas matter and every team member has the opportunity to shape what comes next.
Job Summary Lead comprehensive applications/web development for highly complex projects; typically work as part of a team to implement complex business solutions. Deliver strategic and expert coding; focus on overarching development strategy for a large, complex, multi-faceted application. May manage a number of projects simultaneously.
You will also help us build and scale our GenAI application platform. This platform will be the hub within HBS where GenAI application developers can share their data and code. As custodians of this platform, we intend to use the best practices in the field along with existing repositories to expedite the path from prototype for GenAI applications and unlock economies of scale. You will be highly influential in advancing our GenAI applications and guide teams towards impactful and ethical AI. We seek an expert who is eager to grow and disseminate GenAI model expertise across the organization.
Job-Specific Responsibilities
Build trust and collaboration
by being present on-site and engaging directly with colleagues and various constituents.
Infrastructure Management : Design and manage cloud infrastructure (AWS) optimized for the intensive computational needs of AI and ML workloads.
CI/CD Pipelines : Build and maintain continuous integration and continuous deployment (CI/CD) pipelines tailored for AI/ML models
Automation : Automating model training, testing, deployment, and monitoring processes.
Scalability & Reliability : Ensuring that AI applications are scalable and highly available in production environments.
Monitoring & Observability : Implementing systems to monitor model performance, data drift, logs, and uptime.
Collaboration : Working closely with data scientists, ML engineers, and backend developers to ensure smooth and secure deployment of AI services.
This role is responsible for other duties as assigned
Basic Qualifications
Minimum of seven years' post-secondary education or relevant work experience
Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired
Minimum of five years Dev Ops experience with at least a year of ML Ops and Software Engineering Development background
Cloud Platforms : Proficiency in cloud services - Amazon Web Services (AWS); Nice to have - Google Cloud Platform (GCP), or Microsoft Azure.
Containerization & Orchestration : Expertise with Docker and Kubernetes for managing application environments.
Infrastructure as Code (IaC) : Experience with tools like Terraform or Ansible for automating infrastructure provisioning.
Programming : Strong scripting skills, typically in Python or Go, for automation and building operational tools.
MLOps Tools : Familiarity with MLOps platforms and tools (e.g., MLflow, Kubeflow, Data Version Control (DVC)) is often a plus.
SRE Mindset : A focus on site reliability engineering principles to ensure robust production systems.
Tech Skills : Terraform, GitHub actions, Quadrant, Vector Database, CI/CD, Python, Shell Scripting.
Strong Communication Skills, Good Team Player, ability to wear multiple hats, fast learner, problem solving and go geter attitude.
Additional Information
Appointment End Date:
This position is approved as a term appointment with an end date of June 30, 2027. There is a possibility of renewal/extension.
Standard Hours/Schedule:
40 hours per week
Visa Sponsorship Information:
Harvard University is unable to provide visa sponsorship for this position
Pre-Employment Screening:
Identity, Education, Criminal
Other Information:
This is a hybrid position which we consider to be a combination of remote and onsite work at our Boston, MA based campus. HBS expects all staff to be onsite a minimum of 3 days per week and departments provide onsite coverage Monday Friday. Specific hours and days onsite will be determined by business needs and are subject to change with appropriate advanced notice.
We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role
As part of our evaluation, candidates are required to complete a
Take Home Assignment
after clearing Technical Recruiter Screen. This assignment will test your specific skills/knowledge areas relevant to the role.
A cover letter is required to be considered for this opportunity
Work Format Details This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts . Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.
Salary Grade and Ranges This position is salary grade level 059. Please visit Harvard’s Salary Ranges to view the corresponding salary range and related information.
Benefits
Generous paid time off including parental leave
Medical, dental, and vision health insurance coverage starting on day one
Retirement plans with university contributions
Wellbeing and mental health resources
Support for families and caregivers
Professional development opportunities including tuition assistance and reimbursement
Commuter benefits, discounts and campus perks
Learn more about these and additional benefits on our Benefits & Wellbeing Page .
EEO/Non-Discrimination Commitment Statement Harvard University is committed to equal opportunity and non-discrimination . We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes.
Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy . Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
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Languages
- English
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