Posted today · be early

AI Labs Teaching Expert (Tech Track)

TripleTen

WorldwideremotePosted today

Skill Required

AI-EngineerTechnical-TrainerSoftware-EngineerQA-Automation-EngineerTechnology-FacilitatorAI-Engineering-InstructorAI-Development-InstructorAI-ML-InstructorApplied-AI-Engineering-InstructorAI-InstructorTechnical-AI-TrainerArtificial-Intelligence-InstructorApplied-AI-InstructorAI-Course-InstructorAIsoftware engineeringGitHub ActionsEngineeringR ProgrammingPlaywrightautomationbuildingTestNGdesignGitETLandGenerative AICIParttime

Key highlights

Fully remote collaboration with sessions aligned with CET
Project-based, part-time collaboration

Role overview

Nebius Academy (powered by TripleTen) runs AI Labs: three-hour live online sessions where engineers bring a real repository, pipeline or test suite and leave with a working AI deliverable configured against their own code and standards. We are looking for an AI Labs Teaching Expert to facilitate the Tech Track across our QA and AI-assisted programming courses. You will guide participants through real technical projects, help them make sound architecture and scoping decisions, and support them in producing a working result during the session.

Responsibilities

Review participant project cards before each session and prepare the relevant materials.
Assess the scope of each project and help participants define what can realistically be completed during the Lab.
Work alongside participants as they design, configure and test their AI-assisted development workflows.
Read unfamiliar repositories quickly enough to identify issues and provide actionable guidance.
Help participants debug agent state, routing and behaviour under time pressure.
Guide participants in configuring AI code review, repository-level instructions and agent governance.
Help participants define appropriate automation boundaries, retry limits and human-in-the-loop controls.
Run an engaging online session, move effectively between participant projects and keep the whole group progressing.

Requirements

Production experience integrating AI tooling into a real team’s repository, engineering workflow or CI pipeline.
Experience running an LLM API in a production CI environment, including cost, latency, retry and failure-mode considerations.
Hands-on experience with AI code review, repository-level configuration, agent instructions or AI governance files used by a team.
Strong software engineering background and the ability to understand backend, frontend, ETL, testing and model-related components.
Experience defining automation boundaries, human-in-the-loop gates and safe retry behaviour.
Ability to diagnose whether an agent failure comes from the prompt, routing or state design.
Experience stress-testing AI systems using intentionally incorrect inputs, pull requests or edge cases.
Daily practical use of a coding agent such as Claude Code, Cursor or Codex.
Hands-on experience with CI platforms; strong familiarity with GitHub Actions or a comparable platform.
Practical experience with Playwright.
Production experience with LangGraph and LangSmith.
Experience building or operating multi-agent systems with tracing and evaluation.
Strong live facilitation, coaching or technical knowledge-sharing skills.
Ability to facilitate the current Labs in Russian.
Availability to support the mid-October launch and the planned October–November delivery schedule.

Nice to have

Experience leading an organisation-wide rollout of AI coding tools.
Experience as a Staff or Senior Software Engineer, AI Platform Engineer, QA Automation Architect, SDET Lead, Applied AI Engineer or Forward-Deployed Engineer.
Experience with automated or self-healing test suites.
Experience teaching or facilitating engineers in a live online environment.
Experience working with unfamiliar repositories and technology stacks.
Experience with QA-oriented AI use cases.

Benefits

A project-based, part-time collaboration with Nebius Academy.
The opportunity to work with experienced professionals on real AI-assisted engineering projects.
A practical delivery format focused on working results rather than theoretical demonstrations.
A fully remote collaboration with sessions aligned with CET.
A clear delivery scope for each Lab, including preparation and coordination with the Nebius Academy team.
An opportunity to influence how engineering teams use AI tools safely and effectively in their daily work.