AI Systems Engineering Subject Matter Expert

🤓 Tr ipleTen is an EdTech company that designs and runs tech career learning programs for the US and Latin American markets. We've been doing it for over five years, teaching complete beginners — people with no prior tech background — through cohort-based programs built on our own platform and curriculum, developed in partnership with Nebius AI. Our team is fully remote and globally distributed, and we serve a large, active student base across both regions.

We're building a program for experienced engineers transitioning into system architecture roles. We need AI Systems Engineering practitioners who can do more than just know their craft — they need to help build the curriculum and turn their expertise into content others can learn from.

This is a content authoring role. You'll start by shaping the program syllabus based on our existing draft, then move into producing lessons using AI-gen tools — following our content guidelines, reviewing the output, and fine-tuning it until it's accurate and teachable. An LX designer will review your content and send comments back; you'll iterate from there. The best candidates are people who are opinionated about what good systems engineering looks like and what engineers need to learn, can spot when something is oversimplified or wrong, and are comfortable working in a structured production process and keeping up with deadlines.

Your audience: experienced engineers looking to level up to system architecture roles. They will spot shallow content instantly.
Format: async-first, project-based, estimated 4-6 months. We expect you to be ready to around 15-20 hrs/week.

Areas of expertise
We will bring on three SMEs , each focused on one of the following areas.
SME A — System Foundations, API & Data
Module 1 — Foundations of System Engineering (Architecture principles, OpenTelemetry, distributed systems)
Module 2 — API & Service Architecture (REST, GraphQL, gRPC, service boundaries, DDD)
Module 3 — Data Architecture & Storage Patterns (SQL/NoSQL, sharding, replication, Redis caching)
SME B — Cloud, Distributed Systems
Module 4 — Cloud Infrastructure & Platform Engineering (Kubernetes, Terraform, GitOps, CI/CD, FinOps)
Module 5 — Distributed Systems & Event-Driven Architecture (CAP theorem, event-driven, Kafka, alert routing)
SME C — Security, AI Systems & Architecture Leadership
Module 6 — Security & Compliance Architecture (Zero-trust, threat modeling, compliance, secure CI/CD)
Module 7 — AI Systems Design & Integration (LLM integration, RAG, ML reliability, AI governance)
Module 8 — Architecture Documentation & Leadership (ADRs, C4 diagrams, technical communication)

Please indicate in your application which area fits you best. If you have overlapping skills, don’t hesitate to apply and indicate it in your application. Submit all resumes or CV's in English.

Review and shape the existing syllabus draft — validate topic sequencing, flag gaps or unrealistic scope, and make sure the content reflects how these systems are actually built in production.
Define clear learning objectives per topic: what should a student be able to do after this lesson, not just know.
Produce lessons using AI-gen tools following our content guidelines — then review, fact-check, and fine-tune the output until it's technically sound.
Design hands-on projects and exercises that are realistic for a working engineer studying 20 hrs/week.
Write supporting content: project instructions, rubrics, and reviewer guides.
Respond to LX designer feedback and iterate on content — this is a back-and-forth process, not a one-time handoff.

5+ years of real-world experience as a Senior Systems Engineer
Has designed and shipped systems at scale in a real company — not just coursework or side projects
Can explain why a decision was made, not just how it was implemented
Strong technical communication skills — ability to explain complex topics clearly to learners
Comfortable using AI tools for content draft