AI Systems Engineering Expert

Remote from: USA
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Software Engineering
Employment type: Part Time,
Job posted: 17 Jun 2026
Apply before: 17 Jul 2026
Experience level: Senior
Views / Applies: 16 / 2

TripleTen is the premier online coding bootcamp, renowned for its exceptional completion rate and graduate employment success.

Education Management
2019

Actively Hiring

AI Summary

TripleTen is seeking an AI Systems Engineering Expert to lead live sessions, review student projects, and provide architectural feedback for experienced engineers transitioning into system architecture roles. The role involves running office hours, mock architecture review boards, and setting technical standards for supporting instructors. Candidates need 5+ years of senior experience in system architecture, cloud infrastructure, and distributed systems. This is a part-time, remote teaching position with flexible hours and milestone-based payments.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight The role requires deep senior-level expertise in system architecture and the ability to critique designs live, making it challenging but not the hardest due to structured curriculum and support.

Salary Analysis

AI Insight The offered salary is not specified, but the market median for an AI Systems Engineering Expert in the US is approximately $165,000. Given the part-time nature (15-25 hrs/week), the actual compensation may be prorated. This role's hourly equivalent would be competitive for senior-level consulting or education positions.

Key Skills

System Architecture Cloud Computing Distributed Systems AWS Kubernetes Technical Mentoring System Design DevOps Teaching CI/CD

Cover Letter Sample

Dear Hiring Team at TripleTen,

I am excited to apply for the AI Systems Engineering Expert role. With over 5 years of experience designing and shipping scalable systems at companies like [Your Company], I have deep expertise in system architecture, cloud infrastructure (AWS, Kubernetes, Terraform), and distributed systems. I am passionate about mentoring engineers and have a strong track record of leading technical reviews and architecture discussions.

In my previous role, I conducted live design reviews and guided teams through complex architectural decisions. I am comfortable critiquing designs in real-time and providing actionable feedback. I understand the importance of setting a high technical bar while fostering a collaborative learning environment.

I am eager to bring my hands-on experience to TripleTen's program and help experienced engineers level up to system architecture roles. I look forward to the opportunity to contribute to your mission of digital re-skilling.

Sincerely,
[Your Name]

Possible Interview Questions

How would you approach reviewing a student's system design for a distributed messaging system?

I would first understand their design decisions and trade-offs, then evaluate scalability, fault tolerance, and consistency. I'd provide specific feedback on service boundaries, data partitioning, and failure modes, explaining why a different approach might be more robust.

Describe a time you had to critique a senior engineer's architecture in a live setting.

In a previous role, I led a design review where a colleague proposed a monolithic service for a new feature. I explained the benefits of splitting into microservices for independent scaling and deployment, using concrete examples from our system's performance metrics.

How do you stay current with evolving technologies in AI and system architecture?

I follow key conferences, read engineering blogs from top tech companies, and experiment with new tools in side projects. I also participate in online communities to discuss best practices.

How would you adjust your teaching style for experienced engineers vs. beginners?

I would focus on advanced concepts and trade-offs, using real-world examples and challenging them with complex scenarios. I would avoid oversimplifying and encourage deep discussions on design choices.

Can you explain a situation where you had to escalate a technical issue to a team of supporting instructors?

When a student's project had a subtle concurrency bug that caused inconsistent state, I analyzed the code, identified the root cause, and provided a clear explanation. I then documented the issue for the support team to use as a learning resource.

Description

🤓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 simulated executive-panel presentations, and give structured, senior-level critique
Set the technical standard for a team of supporting instructors who cover questions and first-line review, and act as their escalation point on design and architecture calls

Requirements

5+ years as a senior software/systems architect, platform engineer, or senior backend/infrastructure engineer
Has designed and shipped systems at scale in a real company, not just coursework or side projects
Depth across the architectural spine: system design, API and service architecture, cloud and infrastructure (AWS, Kubernetes, Terraform, CI/CD), and distributed systems
Can explain why a decision was made, not just how it was implemented, and can diagnose and critique someone else’s architecture live
Strong technical communication: comfortable leading a live session and writing clear, specific review feedback
Strong English C1+ — instruction and review are in English for a US-based audience
Comfortable using AI tools in day-to-day technical work

What we can offer you

Milestone-based payments tied to deliverables
Fully remote work with flexible hours
A digital office — we use modern tools (Notion, Miro, Slack, Figma) to keep collaboration smooth
Professional trust and autonomy — no micromanaging
The chance to see real impact: our metric is graduates landing jobs in tech
Join a diverse, international, and close-knit team excited to work with you

Apply now >