AI Software Engineer
Andromeda Robotics
| Company | Andromeda Robotics |
| Category | Engineering |
| Location | South Melbourne |
| Remote | On-site (inferred) |
| Employment | Full-time |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 27 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (workable) |
Description
The Bigger Picture At Andromeda Robotics, we're not just imagining the future of human-robot relationships; we're building it. Abi is the first emotionally intelligent humanoid companion robot, designed to bring care, conversation, and joy to the people who need it most. Backed by investors such as Forerunner and Main Sequence and with customers already deploying Abi across aged care and healthcare, we're scaling fast, and we're doing it with an engineering-first culture that's obsessed with pushing the limits of what's possible. This is a rare opportunity to join a team working on complex, real-world AI and robotics problems that directly shape how Abi shows up in the world. Our Values Empathy – Kindness and compassion are at the heart of everything we do. Play – Play sharpens focus. It keeps us curious, fast and obsessed with the craft. Never Settle – A relentless ambition, bias toward action, and uncomfortable levels of curiosity. Tenacity – Tenacious under pressure, we assume chaos and stay in motion to adapt and progress. Unity – Different minds. Shared mission. No passengers. How You'll Make an Impact Abi’s conversational system is the integration point of the stack, and the most customer-facing engineering surface at Andromeda. We tie several systems together into a cohesive persona, interfacing with firmware, robotics software, onboard machine learning systems and cloud services to turn user input into intelligent, context-aware responses. We maintain Abi’s memories, personality and activities to build an engaging companion for our customers. We're hiring an AI Software Engineer to own meaningful parts of this stack: voice pipeline orchestration, conversational state management, memory and recall systems, and the evaluation and telemetry infrastructure that tells us whether Abi is getting better or worse in the field. This is a hands-on, production-focused role. You'll build systems that run on edge hardware in aged care homes. These are environments with ambient noise, unreliable networks, and real people who depend on Abi working reliably at 3am, not just in a demo. You'll own the instrumentation that measures how well those systems are performing, and use that data to drive what gets built next. You'll work across the full lifecycle: design, implement, instrument, deploy, observe, improve. Your work will directly shape how customers experience Abi and play a central role in the quality, trust, and capability of the company's core product. Requirements Key Responsibilities Develop, debug, and maintain production AI software systems across voice, conversational state, and memory/recall workflows. Own and improve critical parts of the intelligence stack, including turn-taking, conversational state orchestration, memory retrieval, prompt and context window management, and the output behaviours that define Abi's personality in customer interactions. Build and maintain telemetry, instrumentation, and quality metrics across the stack. Use data to identify regressions, measure improvements, and inform prioritisation, not just ship features and hope. Evaluate and integrate voice and language foundation models, making informed tradeoffs between accuracy, latency, cost, and resource consumption on constrained hardware. Improve software quality across reliability, performance, maintainability, and observability, with a bias toward stability in production over velocity in development. Build resilient systems that handle the real world gracefully: ambient noise, partial utterances, network drops, hardware variance, and unexpected power cycles. Communicate clearly, document decisions well, and take ownership of outcomes end-to-end. What We're Looking For 3+ years of software engineering experience, with meaningful time spent building and operating production AI/ML application systems (not research-only). Bonus if those systems were heavily asynchronous or stateful.
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