LEARNING FACILITATOR, Office of the Provost

Learning Facilitator, Office of the Provost

Boston University is launching 3 new online MS programs in Fall 2026 in Computer Science & AI, Software Engineering & AI and Enterprise AI.

We seek candidates who are passionate about delivering a stellar online education experience and a student-centric approach to join our growing Learning Facilitator (LF) team. Experience working with non-traditional students, who are accomplished mid-level and senior-level domestic or international professionals, is a plus. The LF is a valued member of the teaching team and will work closely with the faculty to manage the delivery of the academic content in each module and serve as the main academic touchpoint for the students in the online module.

Responsibilities

Reporting to Program Leadership, the Learning Facilitator (LF) role involves a variety of activities carried out during the delivery of a given course. The goals are to ensure that students receive timely, detailed, and ongoing feedback, consistent with rubrics designed by the Faculty Lead, that student questions and concerns are addressed timely, and that the student learning experience is the best in class within online learning.

This position is 100% remote.

Specific responsibilities include but are not limited to:

• Course Delivery (40%)
• Provide timely recommendations on course content to instructors and students.
• Respond to student questions and concerns in a timely and efficient manner in alignment with BU's student-centric culture.
• Hold regular online office hours to meet with individual students and teams.
• Participate/lead open office hours as needed.
• Monitor and engage in student discussion forums on a weekly basis. Monitor and manage student participation in discussion forums.
• Propose and implement delivery initiatives geared toward student engagement.
• Conduct QA activities as part of module pre-launch.
• Manage team issues in coordination with Faculty and CDS leadership.
• Learner feedback and grading (40%)
• Grade assignments.
• Provide detailed feedback to students on their assignments and overall course performance.
• Contribute to daily operations including late submissions checks, publishing grades, etc.
• Course Improvement (10%)
• Report post-launch issues (defects and enhancements as related to course design or Blackboard issues) as per the established process.
• Share feedback for continuous improvement of the course content.
• Administrative (10%)
• Identify opportunities and define processes to improve operations.
• Provide regular status updates in the team project management dashboard.
• Other relevant duties that support student learning.

Required Skills

Must possess a conferred bachelor's degree. A graduate degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related STEM field is preferred.

2–4 years of relevant professional, technical, teaching, or instructional support experience.

Must demonstrate expertise in at least one of the following three academic areas. Candidates are not expected to possess expertise across all areas.

Required Experience

Data Science / Enterprise AI Competencies

Experience with Python and data science programming using tools such as NumPy, Pandas, scikit-learn, PyTorch, and Matplotlib.

Experience with databases and SQL.

Experience with machine learning and statistical models such as regression, random forests, boosting methods, and neural networks.

Ideally, experience with large-scale data technologies such as Spark, MapReduce, or related big-data platforms.

Computer Science Competencies

Experience with Python, C, Java

Experience with data science programming in Python, system programming using C, networking using python, C or java

Knowledge of systems architecture

Experience with databases and SQL

Ideally, experience with big data tech stacks such as map-reduce, spark, etc.

Experience with code assistants (e.g., copilot)

Experience with machine learning and statistical models such as lasso, ridge, random forests, boosting, neural nets.

Experience with basic optimization techniques (e.g., gradient descent)

Software Engineering Competencies

AI/LLM-aided and agentic development - using AI coding assistants (e.g., GitHub Copilot, Claude Code, Cursor), prompt engineering, and critically evaluating AI-generated code; familiarity with LLM-powered agents and tool/API integration.

Modern software engineering - Git/GitHub workflows, code review, testing, debugging, and CI/CD.

Cloud and distributed systems 0 deploying scalable applications (AWS preferred; GCP/Azure acceptable), containerization, microservices, and observability.

Data systems - SQL, NoSQL, ETL/streaming pipelines, and ML/AI Ops.

Responsible and human-centered AI - usability, explainability, and ethical/security considerations in AI-enabled systems.

Additional Professional Competencies:

Self-motivated with a start-up mindset toward continuous improvement.

Ability to collaborate effectively in a fully remote environment and quickly learn new tools and technologies.

Demonstrated interpersonal, communication, and student-support skills.

Experience managing competing priorities and working with multiple constituencies, including faculty, students, colleagues, and third-party vendors.

Adaptable and comfortable working in a fluid environment.

Ability and desire to mentor or coach students, peers, and colleagues.

Must be able to work a flexible schedule including days, evenings, and weekends.

Desired Competencies

Experience as a Learning Facilitator, Teaching Assistant, Tutor, or similar instructional role.

Experience delivering online learning, preferably in a scaled environment.

Experience working with adult or professional learners.

Experience with learning management systems and tools such as GitHub Classroom, autograders, or similar instructional technologies.

Experience building, deploying, or evaluating AI/LLM-based applications.

Experience creating process documentation, workflows, and best practices.