Role Description 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 commit from 20 to 40 hrs/week. Please submit all resumes or CV's in English. What you will do - 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. Qualifications - 5+ years of real-world experience as a Senior Systems Engineer with depth in your area. - 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 drafting and iteration. - Strong English C1+ — content will be in English for a US-based audience. - Attention to detail, proactivity and ability to meet deadlines independently. Benefits - 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.

• Assess learner project submissions against defined criteria and marking rubrics. • Provide clear, constructive, and developmental written feedback on all assigned assessments. • Apply consistent grading standards aligned with programme calibration and moderation guidelines. • Collaborate with tutors and delivery team members to support marking consistency across cohorts. • Participate in calibration and moderation activities as required during each marking period. • Manage allocated marking workloads to meet agreed turnaround times and deadlines. • Work collaboratively with learner support teams to ensure feedback enables learner progression. • Maintain accurate records of assessment outcomes in relevant learning systems. • Providing further async-specific feedback to learners when requested, post mark & feedback

• Design and manage high performing AI systems • Own the full funnel architecture for AI products • Support and optimise current portfolio while maintaining low latency standards • Act as primary technical resource for new AI initiatives • Ensure seamless transition from raw social signals to finished market insights • Accountable for commercial outcomes of your code

• Diseñar arquitectura de agentes sobre Azure AI Foundry. • Integración con runtimes, pipelines y servicios de datos. • Definir patrones de seguridad y escalabilidad. • Alinear la solución con estándares corporativos. • Validar decisiones tecnológicas.