Founding Systems Architect (Infrastructure; Platform Product)
Location: Flexible (HK p
referred)
Commitment: Part/full-time to start; potential Head of Product/CPO pathway
Compensation: Equity-first, salary to be introduced
Reports to: Founder/CEO
About Arelyx
Arelyx is building human capability infrastructure for the AI age.
As AI reshapes learning and work, technical skills alone are not enough. Students must develop the enduring capabilities that allow them to adapt, judge ethically, communicate clearly, and connect ideas across disciplines.
Through our proprietary REACT framework, Arelyx provides schools with:
A shared language for human capability
A measurable development model
A scalable implementation pathway
We partner with leading schools across Hong Kong and the Greater Bay Area and are expanding across APAC. Our goal is to help schools move beyond fragmented "future skills" initiatives toward disciplined, system-level capability development.
We are building a thoughtful, high-standards team to make this possible.
The Opportunity
You will work closely with the Founder to design how institutions can interpret human development, not just to measure it.
We're seeking a founding system architect leader to design and build the infrastructure layer that makes REACT measurable and scalable.
This role sits at the intersection of learning science, product strategy, research, and data systems. You will translate developmental constructs into structured, longitudinal systems and school-facing tools.
This is an early-stage, builder role. We are looking for someone motivated by long-term impact and comfortable with sweat-equity compensation in pre-funding phase.
What You'll Own
1. Infrastructure Vision
Define what the Arelyx infrastructure platform is and is not
Translate REACT from framework into integrated product ecosystem
Ensure coherence between measurement, interpretation, and application
Ensure conceptual coherence across diagnostics, pathways, dashboards, and school implementation
Position Arelyx as infrastructure rather than a collection of tools
2. Platform Logic & Architecture
Design how the platform modules connect (diagnostic > insight > pathway > reporting)
Define functional requirements for MVP and beyond
Translate Figma concepts into structured product specifications
Ensure platform simplicity despite underlying complexity
3. Product Roadmap & Strategic Direction
Define MVP > V1 > scalable roadmap
Prioritize feature development aligned to infrastructure thesis
Make tradeoffs between rigor, usability, and speed
Identify technical and structural requirements for scaling
4. Measurement Integration (Not Data Execution)
Ensure assessment outputs remain aligned with capability theory
Partner with data and research leads to operationalize analytics models
Establish interpretation boundaries for real-world use
Protect construct clarity as deployment expands
5. Cross-Functional Alignment
Align research, learning, and product layers into one system
Ensure field delivery informs platform evolution
Co-architect long-term infrastructure direction with founder
Represent product thinking in selected partner conversations
What Success Looks Like (12–18 Months)
MVP diagnostic deployed in pilot schools
Functional school dashboard live
Clear, defensible measurement model
Product roadmap aligned to infrastructure vision
Who You Are
Systems thinker with research rigor
Comfortable translating theory into operational environments
Motivated by building foundational infrastructure
Able to operate in early-stage ambiguity
Interested in long-term upside
Role Trajectory
This role is expected to evolve into Head of Product / CPO as the platform and team scale. Early focus is architectural authorship; later focus is product leadership and governance.
You Bring
✓ Background in product, research, or data-intensive systems
✓ Strong grounding in learning science, psychology, or health-related research
✓ Experience building structured assessment or measurement tools
✓ Strategic thinking with hands-on execution ability
✓ Comfort reasoning about how AI-generated outputs should be constrained in decision-sensitive contexts
✓ Comfort in early-stage environments
Bonus
Psychometrics experience
Behavioral / learning / cognitive science
Health or measurement-heavy products
Early infrastructure startups
Health or medical research background
Familiarity with HK / APAC school systems