AI Systems Engineering Expert
TripleTenDescription
At TripleTen, we're building an international platform of digital re-skilling products to help people from diverse backgrounds learn new professions and build sustainable careers in tech.
Our program graduates have landed jobs at top companies like Tesla, Spotify, PlayStation, Google, and Microsoft. So far, over 5,000 students have chosen TripleTen, and hundreds of new students are joining us each month. We believe everyone can jumpstart a new career, which is why we produce quality educational content and offer intensive courses in tech complete with full access to an interactive platform, code reviews, and support from industry practitioners.
We're launching a program for experienced engineers transitioning into system architecture roles. The curriculum is being built by a team of senior authors. What we need now is the person who brings it to life for students: hosts the live sessions, reviews the work, runs the architecture review boards, and sets the technical bar for the people supporting alongside you.
This is a teaching and review role. You'll be the senior technical presence the cohort learns from week to week. You'll run live sessions and office hours, give real architectural feedback on student deliverables, and act as the escalation point for a team of supporting instructors who handle first-line questions. The best person for this is someone who has actually designed and shipped systems at scale, has opinions about what good architecture looks like, and can tell an experienced engineer why their design is wrong, not just whether it runs.
Your audience: experienced engineers leveling up to system architecture roles. Many already write production code daily. They will spot shallow feedback instantly, so the bar here is real seniority, not familiarity.
Format: Async-first with scheduled live sessions. Live sessions and office hours are timed around a US-based cohort. Estimated 15 to 25 hrs/week.
Please submit all resumes or CV's in English.
What you will do
- Host weekly live sessions across the program, focused on the design and decision layer: where to split services, how systems scale and fail, which tradeoff to make and why
- Run group office hours and 1:1 sessions for students working through projects and the capstone
- Review student projects against rubrics: the architecture dossiers, deployed backends, cloud infrastructure, performance reports, security reviews, and the final distributed-system capstone
- Give architectural feedback, not just pass/fail checks. Catch when a design decision is unsound, an interface is wrong, or a scope is unrealistic, and explain the better path
- Run the mock architecture review boards and the
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