[Hiring] AI Engineer @Learning Online Pty

Role Description

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.

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.
• Build and operate production LLM applications:
  • RAG over governed knowledge bases
  • Tool and function calling
  • Structured outputs
  • 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
  • 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
  • Lay the BigQuery foundations for the agent roadmap

Qualifications

• 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

Requirements

• 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

Benefits

• 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

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 R70,000 is 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 R110,000 is 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.