Job Description
Introduction
Most AI roles are a proof of concept that dies in a slide deck.
This one is not.
Learning Online Group is an online education company operating across Australia, Canada, the UK and New Zealand.
Over 100 staff, a portfolio of brands spanning beauty, photography, animal care and tattooing, and a growing amount of the business quietly running on systems our AI function built.
We already have a South African team working alongside our Australian operation, and we are growing it.
This is not aspirational.
We already have LLM-powered document automation, AI-assisted grading and chatbots in production around Salesforce, n8n and Postgres.
What comes next is planned and funded: a Google Cloud data platform on BigQuery, and a multi-agent orchestration layer powering tutoring, student service and analytics agents across every brand.
Somebody has to build that.
We are hoping it is you.
One thing to be clear about upfront: this is a fully remote role working with our Australian team, which means an early start in South Africa.
Be honest with yourself about that before you apply, because the hours are the part people underestimate.
Duties & Responsibilities
You are an engineer first.
Not research, not data science.
You write tested, typed Python, ship behind CI/CD, and own what you run in production.
When it breaks you are the one reading the logs.
You will work across Google, Salesforce, Vonage, Customer.io and WordPress, connected through n8n and custom apps, and increasingly through AI agents and tools like Claude Code and Antigravity.
Depending on where you land in the range, the job looks like this:
Build and operate production LLM applications: RAG over governed knowledge bases, tool and function calling, structured outputs, and multi-agent orchestration where a supervisor agent coordinates specialists
Own evaluation and observability: golden datasets, automated evals for non-deterministic behaviour, tracing, cost and latency monitoring.
If you cannot prove it got better, it did not
Build integrations and semantic data layers across Salesforce, our LMS and finance platforms, with event-driven automation and APIs that other people can actually use
Stand up our Google Cloud AI stack: BigQuery, Cloud Run services in Python (FastAPI), vector search, and the Claude, OpenAI and Gemini APIs
Implement guardrails and responsible AI controls: least-privilege access, prompt-injection defence, privacy-safe data handling
Monitor production, triage failures, and keep the runbooks honest




The first six months are already mapped: take ownership of the live automation estate, ship internally scoped features, take our internal knowledge assistant from design to production in Slack, and lay the BigQuery foundations for the agent roadmap.
Desired Experience & Qualification
We have deliberately advertised one role with a wide band, because we would rather meet valuable people than argue about titles.
Where you land depends on what you have actually shipped.
To be in the conversation at all:
Solid Python, with Git, and enough SQL to check your own results
You have called REST APIs and handled JSON and webhooks in something you built
You have built at least one thing with an LLM API and can explain, in detail, where it breaks.
Personal projects count.
Hackathons count.
"I read about RAG" does not
A degree in computer science, software engineering, AI or data, or the equivalent proven in work
To be at the top of the band:
5+ years software engineering, including 2+ years running LLM or agentic systems in production, where "production" means real users and real consequences
Hands-on RAG: embeddings, vector databases, retrieval design, and the evals that prove quality
Enterprise integration depth: REST, webhooks, OAuth or JWT.
Salesforce experience is a real advantage
Cloud engineering with Docker and CI/CD.
Google Cloud preferred, AWS or Azure welcome
You have set engineering standards for other people and are happy mentoring a less experienced engineer
You can sit with a non-technical department head in another country, work out what they actually need, and translate it into a system
Nice to have at either end: multi-agent frameworks (LangGraph, CrewAI), Model Context Protocol, FastAPI, education sector experience, and previous remote work with an international team.
Some of our strongest applicants come from South African software houses and product teams (Entelect, BBD, DVT, Synthesis, Dariel), local scale-ups and fintechs (Takealot, Yoco, Luno, JUMO, Prodigy Finance, Lula), data and engineering teams inside the big insurers and banks (Discovery, Old Mutual, Standard Bank, Momentum),



or from remote contracting for overseas clients.
What matters most:
Self-directed.
Remote work makes this non-negotiable.
Nobody is going to stand behind you
Motivated by impact.
You want to watch the thing you built change how a business operates
Comfortable with ambiguity.
This function is still being defined and you get a say in it
Commercially minded.
You ask whether the build is worth the time before you start it
Fast learner.
The tooling moves weekly and you enjoy that rather than resenting it
Remote setup requirements:
A private, quiet home workspace
Uncapped fibre internet with a mobile data backup
Backup power (inverter, UPS or generator) able to cover your full working day through load shedding
Your own machine capable of doing real development work
Package & Remuneration
R60,000 to R110,000 per month, and we mean the whole range.
That is deliberately wide, so here is exactly what it means:
Around R60,000 to R70,000is for someone early in their career who has genuinely built with LLM APIs, can work through an integration without hand-holding, and wants to grow fast.
You will work alongside senior engineers, ship with review, and take on more as you prove you can
Around R85,000 to R110,000is for someone who has run production AI systems before, can own the architecture, set the standards, and mentor someone more junior.
You take the function and you run it
If you are somewhere in the middle, apply.
We will work it out together.
Paid monthly in ZAR
Fully remote, work from anywhere in South Africa
Hours aligned to Australian business hours
Engaged as an independent contractor through Remote, our global contracting platform
Why people love this role
Pay at the top end of the South African market for this kind of work
Fully remote.
No commute, no traffic, no office politics
Real scope and hands-on from day one, with real budget and real stakeholders
Direct access to the CTO and leadership team, not five layers of management
Exposure to a $6M+ paid media operation across four markets
Why people stay
We invest in learning.
Tools, courses, conferences, if it makes you better at your job we want to hear about it
We already have a South African team and we treat them as part of the business, not as an outsourced function
You get to build production AI properly, with evals and guardrails, instead of shipping demos
The problems are real operational problems with measurable outcomes
Interested?

📌 Ai Engineer (Melbourne)
🏢 Learning Online Pty
📍 Melbourne