DevOps Engineer, Generative AI , HBS Foundry

Dev Ops Engineer, Generative AI Applications, HBS Foundry

Harvard University – Harvard Business School HBS Foundry – Full-time – Boston – Salary grade 059 – Exempt – Term appointment:
Yes

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.

• 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.

• 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 AWS;
  Nice to have GCP or Microsoft Azure.
• Containerization & Orchestration: Expertise with Docker and Kubernetes.
• Infrastructure as Code (IaC): Experience with Terraform or Ansible.
• Programming: Strong scripting skills in Python or Go.
• MLOps Tools: Familiarity with MLflow, Kubeflow, DVC.
• SRE Mindset: Focus on site reliability engineering principles.
• Tech
  
  Skills:
  
  Terraform, Git Hub actions, Quadrant, Vector Database, CI/CD, Python, Shell Scripting.
• Strong Communication Skills, good team player, ability to wear multiple hats, fast learner, problem solver and go‑getter attitude.

• Appointment End Date: Term appointment with end date June 30, 2027; possibility of renewal.
• Standard Hours/
  
  Schedule:
  
  40 hours per week.
• Visa Sponsorship: Harvard University cannot provide visa sponsorship.
• Pre-Employment Screening: Identity, Education, Criminal.
• Location: Hybrid – combination of remote and onsite work at Boston, MA campus. Minimum three days onsite; specific schedule determined by business needs.
• Candidate interviews may be virtual or in-person.
• Take Home Assignment required after Technical Recruiter screen.
• A cover letter is required to be considered.

This position may be performed at a location outside Harvard that is a Harvard registered state and complies with University Policy. Specific location details discussed during interview. Certain visa types and funding sources may limit work location. Individuals must meet sponsorship requirements before employment.

This position is salary grade 059. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information.

• Generous paid time off including parental leave.
• Medical, dental, and…