About the role

Technical Mentor with expertise in AI mentoring learners through interactive sessions at Udacity. Supporting global learners in understanding advanced AI topics and applications.

Responsibilities

Your responsibilities as a technical mentor will be divided into three major tasks.
1:1 video calls
Virtual Technical Deep-Dive Sessions
Group Q&A sessions
Provide personalized support by addressing learner questions related to course content and projects.
Prior to the call mentors are expected to review the students' previous project submission(s) - provided by the Mentor Success Team when available - and/or any specific areas of the Nanodegree content or project that the student has expressed confusion or difficulty with.
For concept deep-dives, mentors will come prepared with a slide presentation that reviews a Nanodegree concept in more detail, share different use-cases for the concept to broaden student perspectives and understanding, and hold a Q&A session with the learners.
For project walkthroughs, a mentor will come prepared with a slide presentation that outlines each element of the rubric to help learners understand expectations and typical problem areas they may encounter. This can include a mentor “grading” a sample submission to demonstrate what mentors are looking for when reviewing projects.
Host regular sessions (via Slack or video) to address learner queries related to projects and coursework. No prior preparation required.

Proven technical expertise with 5+ years of experience in the relevant field
A passion for mentoring and helping others succeed in their learning
Excellent interpersonal skills. You enjoy building relationships, communicating effectively, and fostering a positive learning environment
A deep understanding of the tech industry and emerging trends in AI and related fields
The flexibility to work part-time as an external contractor alongside your current commitments
Strong understanding of LLMs, prompt engineering, and agentic reasoning frameworks such as CoT and ReAct
Experience designing and implementing prompt chains, role-based prompts, feedback loops, and iterative prompt refinement
Hands-on experience building agentic workflows, including task routing, orchestration, sequential workflows, parallel workflows, and reflective AI workflows
Ability to design and implement AI agents with tool use, API integrations, structured outputs, memory, state management, and database interaction
Experience with RAG-based agent systems, including single-agent and multi-agent RAG implementations
Knowledge of AI agent evaluation, including testing, debugging, and improving agent performance
Understanding of multi-agent system design, including orchestration, routing, state coordination, and multi-agent architectures
Ability to explain complex Agentic AI concepts clearly through instruction, demos, and learner support.

Make an impact by mentoring and contributing to a vibrant, global learning community
Showcase your expertise and gain recognition for your technical knowledge
Learn and network with our global community of mentors while staying ahead of the curve on cutting-edge technologies
Earn additional income with the flexibility to work on your own schedule