Learning Systems Engineer

peopleworth; Cape Town; On-site; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Collaborative, people-centered perfomm

Opportunities to grow in a fast-paced

Meaningful work supporting dependable

Job summary

peopleworth is seeking a Learning Systems Engineer to safeguard the technical integrity of an AI engineering learning programme. This hands-on role focuses on verifying, maintaining and supporting the technical systems through which learning is built and delivered.

You will work with Learning Experience Designers and developers to ensure reproducible environments, test integrations, and provide front-line support during live sessions while promoting responsible use of AI tools.

Qualifications

• Demonstrated experience in software testing, quality assurance or related engineering role.
• Strong ability to read, run, test and debug code written by other developers.
• Proficiency with Python and confident troubleshooting dependency, configuration and runtime issues.
• Practical understanding of AI patterns, including LLM APIs and agent-based workflows.
• Familiarity with Git-based development workflows, repository management and CI/CD practices.
• Experience configuring and troubleshooting developer environments, APIs, databases and system integrations.
• Strong systems-thinking with ability to identify dependencies, risks and failure modes across a technical toolchain.
• Experience using AI-assisted development tools and supporting non-technical colleagues in adopting them.
• Clear, patient communication and ability to support learners during live delivery.
• Calm, responsive approach to resolving technical issues under pressure.

Responsibilities

• Verify that code, activities and model solutions run end-to-end in the target environment before content review.
• Test integrations between learning storyboards, code, repositories, learner environments and Canvas LMS.
• Identify gaps and failure points where learning content, code and platform components connect.
• Set up and maintain learner repositories, environment configurations and developer tooling across cohorts.
• Ensure learner environments remain stable, reproducible and version-controlled during development and live delivery.
• Define technical acceptance criteria for external contributors and review outputs against those standards.
• Provide front-line technical support to learners during live delivery, diagnosing issues in real time.
• Respond rapidly to incidents during delivery windows to minimise disruption.
• Coach Learning Experience Designers to use Git and AI-assisted workflows confidently.
• Build lightweight automations and AI-assisted routines to reduce repetitive testing and build actions.
• Contribute technical input into decisions about portfolio publishing and development environments.

Skills

Software testing

Code debugging

Technical communication

Learner support

Tools

Python

Git-based workflows

APIs

PostgreSQL

CI/CD

Render

Google Cloud Run

GitLab CI/CD

LLM APIs

Claude

Canvas LMS

Job description

Intro

At peopleworth, we support work where people and performance thrive. As part of our Employer Group, we work with a variety of forward-thinking partners and are excited to share this opportunity that sits within our growing group.

Intro

At peopleworth, we support work where people and performance thrive. As part of our Employer Group, we work with a variety of forward-thinking partners and are excited to share this opportunity that sits within our growing group.

Role Overview

The Learning Systems Engineer will safeguard the technical integrity of an AI Engineering learning programme, ensuring that code, integrations and learner development environments are reliable, reproducible and ready for delivery. This is a hands-on technical assurance and support role for someone who combines strong engineering discipline with patience, clear communication and a genuine interest in education. The role does not own subject-matter expertise or curriculum authorship. Its focus is to verify, maintain and support the technical systems through which learning is built and delivered.

Key Responsibilities

• 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

• 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

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

Our Recruitment Process

• Application Submission: Complete the online form and answer brief application questions
• Initial Screening: Your application is reviewed for role alignment; successful candidates move to the longlist
• Video Interview Stage: You'll be invited to record short responses to 3-4 role-specific questions
• Live Interviews: Shortlisted candidates join first-round interviews (and, where applicable, second or third rounds depending on the role)
• Final Shortlist & Verification: Reference and background checks are completed
• Offer & Contracting: Successful candidates receive formal offers and contract documents
• Pre-boarding & Onboarding: Once accepted, you'll complete a pre-boarding process before officially joining your employing organisation within the Employer Group

Throughout every stage, we value clear communication, respectful engagement, and timely feedback.