[Remote] REMOTE Technical Instructional Designer, AI Programming (Software Engineering Audience)

Note: The job is a remote job and is open to candidates in USA. CapeTalent connects AI-forward Learning and Development professionals with Fortune 100 companies shaping the future. The Technical Instructional Designer will support AI programming curricula for software engineering audiences by evaluating technical accuracy, identifying and filling content gaps, and improving curriculum development processes. The role collaborates with engineering teams, platform owners, architects, developer advocates, L&D professionals, and technical writers to create rigorous, practical learning content.

Responsibilities

• Review Content as a Developer: Evaluate AI programming curricula for technical accuracy, depth, and relevance — from the perspective of the full-stack, front-end, and back-end engineers the training is built for. Act as the trusted technical voice ensuring content reflects how AI systems and real engineering work actually fit together
• Find the Gaps: Use your software engineering background to spot what's missing, outdated, oversimplified, or misleading — the gaps a non-engineer reviewer would miss — and flag or close them
• Fill Content Gaps: When a missing or thin area is identified, develop the technical content to close it — written guides, video tutorials, hands-on labs, technical demos, code examples, and reference material — grounded in real engineering use and delivered for both self-paced and instructor-led formats
• Improve How Content Gets Built: Identify and implement new processes, tooling, and AI-assisted workflows to speed up the design and development phases and raise the quality bar across the team
• Iterate on Feedback: Review feedback from learners, SMEs, and engineering partners, then take the steps to correct errors, improve clarity, and keep content quality high as platforms and tools change
• Provide Context & Intuition: Help the training team understand and surface the underlying context, edge cases, and practitioner intuition that should be embedded in training but is easy to miss without deep hands-on experience
• Translate Complexity: Make sophisticated AI/ML concepts accessible to a technical audience without oversimplifying or losing rigor
• Embed with Engineering Teams: Act as an early tester and end-user by embedding within engineering teams. Collaborate directly with platform owners and architects to understand new technologies from the developer's perspective, then carry that understanding into the training
• Collaborate Across Teams: Work alongside developer advocates, L&D team members, and technical writers to develop and implement a holistic curriculum, keeping it technically sound and current as the field moves

Skills

• 4+ years of hands-on software engineering experience — full-stack web development or general software engineering (front-end and back-end)
• You've shipped real code
• Deep, hands-on technical expertise in AI/ML — e.g., machine learning, deep learning, LLMs, data science, or applied AI engineering
• Proficient programming and debugging in Python (and SQL where relevant), familiarity with common frameworks and tooling (e.g., PyTorch, TensorFlow, or LLM/agent frameworks), standard software development lifecycle practices (Git, testing, modularization), and at least one major cloud provider (AWS, Azure, or GCP)
• Demonstrated ability to evaluate technical content for accuracy and to identify what's missing, outdated, or misleading from an engineer's point of view
• Able to learn new technologies and platforms quickly, and comfortable making data-driven decisions about what content needs to change
• Experience implementing or improving processes, tooling, or AI-assisted workflows to make content development faster and better
• Experience explaining or teaching technical concepts to engineering audiences — through mentorship, internal enablement, talks, documentation, writing, or formal training
• Strong written communication; able to produce clear technical content, including code examples, when gaps need filling
• Portfolio REQUIRED
• Prior experience as an AI Learning & Enablement expert — someone who can not only advise on technical accuracy but also help shape how AI concepts get taught and adopted at scale
• Background in instructional design or corporate technical training
• Familiarity with e-Learning tools (e.g., Articulate Storyline, Rise) and Learning Management Systems (LMS)
• Experience embedding with engineering or platform teams as a technical advisor

Benefits

• 6-month contract (strong likelihood of extension)
• 100% Remote (U.S. or Canadian candidates only)
• Laptop provided

Company Overview