About Aphex
We're the construction execution platform replacing outdated spreadsheets with multiplayer tools that delivery teams love. Major contractors like Acciona, CPB Contractors, John Holland, and McConnell Dowell use Aphex to deliver projects from £50 million to multi-billion pound mega projects.
We're market-leading in Australia and the UK, supporting teams building the roads, rail, tunnels, and hospitals that millions use every day. We're leaning further into AI as a core part of where the product goes next, and we've started building the foundational pieces.
Construction has been underserved by technology for decades, and it's now at real risk of being left behind by AI. We don't intend to let that happen. Aphex builds the orchestration layer the world's major construction projects run on, and AI is central to where we take it next. This role is for someone who wants to be at the heart of that, not just shipping AI features, but helping shape how an entire industry puts AI to work.
You'll start hands-on, building and shipping our AI features in the real product. From there it grows. As you learn what works, you'll help set the standard for how we build, evaluate and monitor AI across Aphex. Practical first, then broadening into the bigger picture.
What You'll Do
Build and implement
Translate briefs into working AI features, selecting the right model and implementation approach for the use case
Test inputs and outputs before shipping
Ship AI features into the real product
Evaluation and reliability
Monitor and evaluate AI feature performance in production
Dig into real inputs and outputs to find where prompts or implementations can be better
Keep every AI feature across the platform accurate and reliable over time
Build the evaluation coverage that catches regressions before users do
Improve and iterate
Refine prompts and implementations based on how features actually behave in the wild
Research evaluation and implementation techniques, and bring recommendations, not just problems
Decide what good looks like and measure it systematically
About You
Essential:
You can explain technical concepts, tradeoffs, and constraints clearly in close 1-on-1 work
You take ownership of what you build and keep it working over time, rather than shipping and moving on
Strong written and verbal communication for async, cross-timezone collaboration
Highly valued:
Hands-on experience building LLM-based features and evaluating them in production: LLM APIs, prompt engineering, handling AI outputs, iterating on real results
Shipped AI features to real users and handled the monitoring, debugging, and iteration that follows
Familiarity with LLM evaluation frameworks and tooling such as LangSmith or equivalent
Familiarity with RAG, vector databases, or similar techniques (or the fundamentals to pick them up fast)
Full-stack TypeScript/React (the role may grow to include implementation over time)
A habit of staying current with AI and judging when a new technique is actually worth adopting
Not looking for:
Build-and-forget engineers who ship AI features and never check whether they're working
People who want to work in isolation rather than in close daily partnership
Candidates targeting senior architect, pure research, or team-lead roles. This is a hands-on, mid-level role
Why This Matters
The people using Aphex are time-poor. They're planners, engineers, and project managers running billion-pound projects, and every minute our AI saves them is time back in their day. The AI we're building needs to be accurate and reliable, every day, on real project data. Building AI features is one thing. Keeping them genuinely working once real users depend on them is what turns a valuable feature into something construction teams rely on every day.
What We Offer
Work & Culture
Remote-first role with a thriving Philippines-based engineering team
Annual team offsite, all expenses paid, to connect in person
Online socials with an Airwallex card for team lunches and activities
Time Off & Wellbeing
20 days PTO + Philippine public holidays (all paid)
5 days sick leave (plus discretionary extra as needed, we're humans, not machines)
Comprehensive private healthcare with family plan option
₱2,000 monthly rice allowance
Interview & Application Process
A few stages to make sure it's a great fit on both sides: a brief one-way video screening on Willo (a few minutes), a coding challenge, then two Google Meet conversations with the team. We'll guide you through each step.
