AI Labs Teaching Expert (Tech Track)

• 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.

• 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.

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.

• 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.

• 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.

Originally posted on Himalayas