---
title: 'AI Software Engineer (Front End) at Maincode'
canonical: 'https://feeny.ai/job/ai-software-engineer-front-end-maincode-melbourne-e5hn8kjce3ba'
type: 'job'
last_seen: '2026-09-11'
---

# AI Software Engineer (Front End) at Maincode

- **Company:** Maincode
- **Location:** Melbourne, Australia
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-03-05
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/maincode/94baa206-3a18-4386-95de-d99fd9b1e196

## Job description

## About the role

Maincode is training the next version of Matilda, the first large language model built and trained from scratch in Australia. We are now scaling the model and deploying it as a live production system.

To do that, we build AI systems from first principles. We design the architectures, run the infrastructure, shape the training process, and operate the systems that serve our models.

Matilda is a production system, not a research prototype, built to be deployed and served for open public access. If the training stack is how Matilda learns, the product is how people experience it. This role sits directly in that delivery layer.

You will build the front end systems that make Matilda usable, fast, and trustworthy for real users. You will work on the interfaces that turn a model into a product: streaming responses, conversation state, safety UX, performance, reliability, and the tooling that helps the team iterate quickly.

## What you would actually do

You will build and maintain the front end systems that power Matilda’s public product and internal tools.This includes:

- Building the core web interface for interacting with Matilda (chat, sessions, history, settings)
- Implementing fast, reliable streaming UX for model outputs (real-time tokens, partial results, cancellation, retries)
- Designing and building UI workflows that support safe and responsible use (reporting, refusals, user feedback, content handling)
- Working closely with backend and infra engineers to integrate APIs, auth, rate limits, and observability
- Improving performance across the app (latency, bundle size, rendering, perceived responsiveness)
- Building internal dashboards and tools that help the team operate the system (usage, quality signals, feedback triage)
- Debugging issues across browsers, devices, networks, and production environments
- Raising the bar on quality through testing, monitoring, and careful rollout practices

You will spend time in code, UI state, performance traces, and production metrics.

The kind of person who does well here We are looking for engineers early in their careers who want to build the product surface of a frontier model, and who care about quality and reliability in real production environments. You may have one or two years of experience building production software. What matters most is curiosity, taste, and the willingness to learn how these systems behave with real users.

People who tend to do well here:

- Care about performance, UX quality, and edge cases that show up in production
- Enjoy building clean, maintainable front end systems, not just one-off screens
- Have strong debugging instincts and do not panic when something breaks
- Think clearly about product tradeoffs, reliability, and failure modes
- Pay attention to metrics and user feedback, not just what looks good locally
- Want to work close to the core system, not just build a marketing site

You do not need prior experience working on AI products. What matters is intellectual curiosity, persistence, and the ability to learn quickly.

## How you would work

You will write production code that sits in the product layer of the Matilda stack. You should be comfortable:

- Working in TypeScript and modern front end tooling
- Building production web applications (component architecture, state management, API integration)
- Implementing real-time or streaming experiences (for example, via SSE or WebSockets)
- Debugging complex UI state and issues that only occur under real conditions
- Collaborating closely with user research, backend, infrastructure, and research teams

Much of the work sits between product and the underlying model. The model evolves quickly, but the user experience must remain stable. You will be working on the front end systems that ship Matilda to the public and help operate it day to day.

## Why Maincode

Maincode builds AI systems end to end. We prepare the data, design the training process, run the infrastructure, and operate the models ourselves. You will work with a small team that:

- Builds the full AI stack rather than outsourcing it
- Treats product quality and reliability as part of the intelligence system itself
- Values engineers who want to understand how things actually work
- Is building long-term capability in training, deploying, and operating large models

If you want to build the product surface of a model trained from scratch, and ship it to real users, you will be close to the core work here.

Note This is a full time role based in Melbourne, working closely with our in person engineering and research team. At this time we are not able to offer visa sponsorship, so applicants must have existing and unrestricted work rights in Australia.

## About Maincode

## Company Overview
- **One-liner**: Maincode is an Australian AI research and product company building Matilda, an intelligent assistant that understands context, learns your workflow, and helps you move faster and more safely.
- **Entity Type**: Private (Bootstrapped – no external funding rounds disclosed)
- **Headquarters**: Melbourne, Australia
- **Founded**: Not publicly disclosed (recent high-growth signals suggest founding around 2024–2025)
- **Founders**: Not publicly disclosed (Dave L. is listed as Chief Coder; founder status unclear)

## Core Business
- **Primary industries**: AI research, applied intelligence, product development for enterprise and knowledge workers.
- **Target customers**: B2B (teams and individuals needing a nuanced, safe AI assistant), researchers, and developers.
- **Mission**: “AI that earns trust in the real world, to move humans forward.” Focus on safe, transparent, and helpful AI systems.

## Products & Services
- **Matilda** (flagship product, private beta 2026): AI assistant with deep contextual understanding across long conversations, multi-step reasoning (inspectable steps), proactive but permission-asking behavior, learning of user workflows over time. Built and hosted in Australia, aligned with Australian privacy standards.
- **Maincoder** (open-source 1B parameter model, released Dec 2025): Code generation and transformation model optimized for low latency and cost.
- **AI Research Residency** (3–6 month paid program): For late-stage PhD students and early-career researchers. Provides access to Maincode’s GPU cluster, infrastructure, and direct collaboration with the core team; aims to publish at top-tier venues.
- **Inference infrastructure (MC-2 cluster)**: High‑availability, sub-200ms global latency inference using custom batching, model sharding, dynamic routing (CUDA, Kubernetes, Terraform, GCP, vLLM, AMD Instinct GPUs).
- **Context Engine & Action Layer**: Proprietary frameworks for long-context reasoning and agentic tool-use/sandboxed execution (turning Matilda from chatbot to agent).
- **Eval Suite**: Internal evaluation framework for model capability, safety alignment, task completion (10K+ scenarios, automated regression).

## Market Standing
- **Valuation / Market Cap**: Not disclosed.
- **Key Metric**: Total funding not disclosed (appears bootstrapped). Headcount: 17 employees (+360% YoY). Monthly website visits: ~14,071 (+116.3% monthly, +56,184% yearly).
- **Notable Investors/Partners**:
  - Demonstrating first agentic payment transaction in Australia with **Mastercard** at the Australian Open 2026.
  - Benchmarking study with **Heidi Health** (cloud vs on‑premise inference).
- **Growth Signals**:
  - 10 active job postings (quarterly increase +42.9%, yearly +150%).
  - LinkedIn followers: 4,468 (+315.6% yearly).
  - Traffic growth (56,184% yearly) and strong inbound interest from US (72%) and Australia (28%).
  - Partnership with Mastercard for a live agentic payment demo signals enterprise traction.

## Competitive Advantages
- **Australian privacy by design**: Infrastructure and model behaviour aligned with Australian standards; transparency and user control emphasized.
- **Research‑to‑production pipeline**: Tight integration between frontier research and a shipped product (Matilda). The research residency directly feeds into product improvements.
- **Agentic safety**: Multi-step reasoning with visible steps, permission‑asking before action, and sandboxed execution – differentiating from black‑box chatbots.
- **Own GPU hardware**: MC-2 cluster (AMD Instinct) allows full control over inference latency and cost.
- **Talent magnet**: Small, high‑agency team attracts PhD‑level researchers with promise of publications and access to SOTA compute.

## Strategic Focus
- Scale Matilda’s user base (currently private beta) and move toward general availability.
- Deepen research in safety & alignment, long‑context reasoning, multimodal perception, agent orchestration, and model efficiency.
- Expand enterprise partnerships (evidenced by Mastercard, Heidi Health).
- Continue growing the team across engineering and research (10 open roles across infrastructure, product, and research).

## Why Work Here
- **Culture**: “Small team doing hard things.” High ownership, move fast, ship without permission. Values: ownership, gradient (fast learning), range, speed, taste, humility. No ego, mission‑first.
- **Work environment**: On‑site in Melbourne, Australia (some hybrid/remote possible with visits). Emphasis on craft and shipping.
- **Research perks**: For researchers – paid residency, ability to publish at top venues (NeurIPS, etc.), access to dedicated GPU cluster, direct line to production.
- **Engineering focus**: Modern tech stack (Python, PyTorch, CUDA, Kubernetes, Terraform, GCP); engineers work on inference infrastructure, model training, safety evals, and product features.
- **Growth opportunity**: From 17 people to planned expansion; early employees can shape the direction of the product and research agenda.

## Sources
1. [maincode.com](https://maincode.com/) – Company website, product description, culture page
2. [LinkedIn – Maincode](https://au.linkedin.com/company/maincodehq) – Headcount, growth metrics, partner announcements
3. [Built In – Maincode Careers](https://builtin.com/company/maincode) – Culture summary and active job listings
4. [AI Directory – Maincode Pty Ltd](https://aidirectory.industry.gov.au/organisation/maincode-pty-ltd) – Business area and location verification
5. [maincode.com/platform](https://maincode.com/platform) – Detailed product and research area descriptions

## Other roles at Maincode

- [Talent Sourcer](https://feeny.ai/job/talent-sourcer-maincode-melbourne-1y96x7ezwa0f) — Melbourne, Australia
- [Psychology Researcher, Talent](https://feeny.ai/job/psychology-researcher-talent-maincode-melbourne-a14qj2zc6b6c) — Melbourne, Australia
- [Forward-Deployed AI Engineer, Justice and Community Safety](https://feeny.ai/job/forward-deployed-ai-engineer-justice-and-community-safety-maincode-melbourne-72q4z3ny2v3d) — Melbourne, Australia
- [Marketing Lead](https://feeny.ai/job/marketing-lead-maincode-melbourne-ejevmh3kfx3n) — Melbourne, Australia
- [Forward-Deployed AI Engineer, Government and National Security](https://feeny.ai/job/forward-deployed-ai-engineer-government-and-national-security-maincode-canberra-hxax53shgchj) — Canberra, Australia
- [Junior Commercial Counsel (AI & Technology)](https://feeny.ai/job/junior-commercial-counsel-ai-technology-maincode-melbourne-axbjnskc6y8h) — Melbourne, Australia
- [Talent Engineer](https://feeny.ai/job/talent-engineer-maincode-australia-kcyvhegegmtk) — Australia
- [Software Engineer](https://feeny.ai/job/software-engineer-maincode-seattle-8wcyg274fjcr) — Seattle, WA
- [AI Research Resident](https://feeny.ai/job/ai-research-resident-maincode-australia-ketgdbs6fjy8) — Australia
- [Research Engineer – Matilda](https://feeny.ai/job/research-engineer-matilda-maincode-melbourne-37p38pkx99xk) — Melbourne, Australia