Technical AI Learning Architect

Role Summary
The Technical AI SME / Learning Architect is responsible for ensuring the AI Builder curriculum is technically credible, practically useful, and grounded in real-world AI product development.

You will work alongside instructional designers, producers, and facilitators to translate complex AI engineering concepts into learning experiences that genuinely help technical builders develop production-grade AI
solutions.

This role is not about academic theory. It is about practical expertise, clear thinking, and helping shape learning experiences that reflect how modern AI products are actually built.

The role directly supports the builder learning pathway outlined in the project brief, including APIs, agents, evals, RAG, production optimisation, and hands-on labs.

Technical Learning & Curriculum Guidance
Help shape and validate technical learning experiences across the builder pathway, including:
● APIs and developer workflows
● Agents and agentic systems
● RAG pipelines and retrieval quality
● Evals and production readiness
● AI application architecture
● Production optimisation, latency, cost, and reliability trade-offs
● Codex workflows and developer tooling

Translate technical complexity into clear, practical learning moments without oversimplifying the reality of production AI systems.

Review existing labs, repositories, demos, and workshop materials to ensure technical accuracy and learner usefulness.

Support the design of practical exercises, challenge labs, and realistic implementation scenarios that mirror how builders actually work.

Technical Credibility & QA
Act as a technical quality bar across curriculum and delivery materials.
Review:
● Code examples
● Lab instructions
● Technical walkthroughs
● Architecture diagrams
● Demo environments
● AI-generated learning content

Flag technical inaccuracies, outdated patterns, unrealistic workflows, or oversimplified explanations early.

Help the wider production team understand where technical nuance matters and where simplification is appropriate for learning.

Cross-Functional Collaboration

Work closely with:
● Instructional designers
● E-learning developers
● Creative and video teams
● Live facilitators
● Technical stakeholders
● Product and enablement leads

Support presenters and facilitators with technical preparation for live and virtual bootcamps.

Contribute to a coherent learning journey across self-paced modules, live delivery, and hands-on labs.

Co-working with AI (required)
You should be highly confident using AI tools as part of your workflow and technical thinking process.

Use AI thoughtfully to:
● Accelerate prototyping and experimentation
● Explore technical approaches and architectures
● Generate and refine technical examples
● Improve documentation and explanation clarity

● Test and validate workflows

Critically evaluate AI-generated outputs rather than accepting them at face value.

Share repeatable workflows, prompts, and approaches that improve team quality and speed.

Requirements
Must Have
● Deep practical experience building or supporting AI-enabled products or platforms
● Experience with APIs, Codex, or AI developer tooling
● Strong understanding of modern AI application architecture and developer workflows
● Hands-on familiarity with APIs, agents, evals, RAG, vector stores, and production AI systems
● Ability to explain complex technical concepts clearly to mixed audiences
● Experience reviewing or shaping technical learning, enablement, or developer education content
● Strong judgment on what is technically credible versus performative or overhyped
Bonus
● Experience running technical workshops, bootcamps, or developer education
● Familiarity with production AI evaluation and observability approaches
● Experience contributing to technical curriculum or labs

Ways of Working (what will help you thrive)
Practical and credible | You care about whether something would genuinely help a builder in the real world, not whether it simply sounds impressive.
Clear thinker | You simplify complexity without losing technical truth.
Collaborative expert | You can work effectively with non-technical creative, learning, and production
teams.
Calm in ambiguity | You’re comfortable shaping emerging ideas and evolving systems in fast-moving environments.