Learning Systems Engineer

peopleworth

Learning Systems Engineer at peopleworth safeguarding the technical integrity of AI Engineering learning programmes. Validating code, integrations and supporting technical environments for effective learning delivery.

Posted 7/22/2026full-timeRemote • 🇿🇦 South AfricaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Proficiency in software testing, technical quality assurance, and code review, with a strong focus on Python and Git-based workflows. Ability to support non-technical colleagues in adopting AI-assisted development tools while ensuring stable and reproducible learner environments.

Highest-signal resume keywords

Software TestingTechnical Quality AssurancePython ProficiencyGit-Based Development WorkflowsAI Application Patterns

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software TestingCode ReviewPython ProficiencyAPI ConfigurationDatabase TroubleshootingContinuous IntegrationContinuous DeploymentSystems ThinkingTechnical SupportAutomation Development

Soft Skills

Clear CommunicationPatient SupportCalm Under PressureCoaching Non-Technical ColleaguesInterest in Learning and Education

Tools & Technologies

GitGitLabGitHubPostgreSQLGoogle Cloud RunCanvasH5PStreamlitAI-Assisted Development ToolsLarge Language Model APIs

Industry Keywords

Learning Management SystemTechnical ToolchainIntegration TestingEnvironment ConfigurationVersion Control

Tech Stack

Tools & technologies

CloudPostgresPython

About the role

Key responsibilities & impact

Verify that code, technical activities and model solutions run successfully from end to end in the approved target environment before progressing to formal content and academic review
Test integrations between learning storyboards, externally developed code, repositories, learner environments and the Canvas learning management system
Identify technical gaps, dependency issues and failure points where learning content, code and platform components connect
Set up and maintain learner repositories, environment configurations, API connections and supporting developer tooling across cohorts
Ensure learner environments remain stable, reproducible and appropriately version-controlled throughout development and live delivery
Define clear technical acceptance criteria for work produced by external technical contributors and review outputs against those standards
Provide front-line technical support to learners during live delivery, diagnosing and resolving environment, code and integration issues in real time
Respond rapidly to technical incidents during delivery windows so that learning sessions can continue with minimal disruption
Coach Learning Experience Designers and other non-technical colleagues to use Git, AI-assisted workflows and developer environments confidently in their day-to-day work
Build lightweight internal automations and AI-assisted routines that reduce repetitive testing, validation and build activities
Contribute practical technical input into decisions about portfolio publishing, development environments and other elements of the learning technology stack

Requirements

What you’ll need

Demonstrated experience in software testing, technical quality assurance, code review or a closely related engineering role
Strong ability to read, run, test and debug code written by other developers
Proficiency with Python and confidence troubleshooting dependency, configuration and runtime issues
Practical understanding of AI application patterns, including large language model APIs, retrieval-augmented generation and agent-based workflows
Proficiency with Git-based development workflows, repository management and continuous integration and deployment practices
Experience configuring and troubleshooting developer environments, APIs, databases, hosting services and system integrations
Strong systems-thinking capability, with the ability to identify dependencies, risks and likely failure modes across a technical toolchain
Experience using AI-assisted development tools and the ability to support non-technical colleagues in adopting them responsibly
Clear, patient communication skills and confidence supporting learners and stakeholders during time-sensitive live delivery
A calm and responsive approach to resolving technical issues under pressure
A genuine interest in learning, education and the effective use of technology to support learner outcomes
Experience with some of the following would be valuable: GitLab, GitLab CI/CD, GitLab Duo, Claude, Claude Code, Python 3.12, uv, PostgreSQL, pgvector, Render, Google Cloud Run, Streamlit, Canvas, LLM APIs, H5P, GitLab Pages or GitHub Pages

Benefits

Comp & perks

Collaborative, people-centered performance culture.
Opportunities to grow in a fast-paced environment.
Meaningful work supporting dependable and accessible learning experiences.