DevOps Engineer, Generative AI , HBS Foundry

Overview

Dev Ops Engineer, Generative AI Applications, HBS Foundry

Description (harboring details omitted for clarity in formatting).

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

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 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 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 guide teams towards impactful and ethical AI 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 AI/ML workloads.
• CI/CD Pipelines
  :
  Build and maintain continuous integration and continuous deployment (CI/CD) pipelines tailored for AI/ML models.
• Automation
  :
  Automate model training, testing, deployment, and monitoring processes.
• Scalability & Reliability
  :
  Ensure AI applications are scalable and highly available in production environments.
• Monitoring & Observability
  :
  Implement systems to monitor model performance, data drift, logs, and uptime.
• Collaboration
  :
  Work 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 AWS;
  Nice to have GCP or Azure
• Containerization & Orchestration
  :
  Docker and Kubernetes
• Infrastructure as Code (IaC):
  Terraform or Ansible
• Programming
  :
  Scripting in Python or Go
• MLOps Tools
  :
  Familiarity with MLflow, Kubeflow, DVC
• SRE Mindset
  :
  Focus on site reliability engineering
• Tech Skills
  :
  Terraform, Git Hub Actions, Vector Database, CI/CD, Python, Shell Scripting
• Strong communication, teamwork, adaptability, problem solving

• Appointment End Date
  :
  Term appointment ending June 30, 2027; renewal/extension possible
• Standard Hours/Schedule
  : 40 hours per week
• Visa Sponsorship
  :
  Harvard University is unable to provide visa sponsorship for this position
• Pre-Employment Screening
  :
  Identity, Education, Criminal
• Hybrid Work
  :
  Hybrid position; on-site requirement at Boston campus minimum 3 days/week
• Take Home Assignment
  :
  Candidates may be required to complete a take-home assignment
• Cover Letter
  : A cover letter is required

Benefits include generous paid time off, health insurance, retirement plans, wellbeing resources, family support, professional development, and commuter benefits.

EEO/Non-Discrimination Commitment

Harvard University is an equal opportunity employer. We prohibit 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.

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