Assignment description
Our Customer is building next-generation products for maths learning across both home and school environments. They are developing a greenfield, adaptive learning platform for kids aged 7–12. Built alongside their flagship product, this from-scratch initiative leverages data and AI to personalize study flows, adjust learning speeds, and deliver tailored educational challenges.

As an Architect / Tech Lead, you will own the core architecture across web, mobile, and backend surfaces while setting technical direction alongside full-stack engineers and reporting directly to the COO/CTO.

Architecture & Direction:
– Own core architectural decisions for a multi-surface platform and set engineering standards across the stack.
Learner Signal Engineering:
– Build, capture, and tune Python-based pipelines and adaptive algorithms that transform raw interaction data into personalized learning paths.
AI Workflow Integration:
– Hands-on setup and management of AWS/cloud infrastructure optimized for AI workflows, establishing best practices for agentic software development.
Collaborative Execution:
– Work closely with the engineering team to direct implementation, review code, and maintain high technical quality.

About the team
You will join a flat, highly autonomous product team with no management layers.
The role is purely product-development focused, not focused on people management, giving you direct influence over long-term technical decisions.

Must haves
– Deep experience architecting modern TypeScript systems at a senior/staff level.
– Strong Python skills focused on data processing and analysis.
– Direct experience with learner signal engineering, adaptive algorithms, or parameter tuning for personalization.
– Substantial hands-on experience using AI-agentic development workflows as a primary mode of engineering.
– Practical experience configuring AWS/cloud environments for AI workflows.

Other requirements
– Strong verbal and written English communication skills for clear, proactive technical collaboration.
– Pragmatic mindset—focusing on shipping simple, robust solutions and practical user value over over-engineering.
– Product-first mindset with a clear preference for hands-on execution over administrative management.
– High autonomy and self-direction suitable for an engineering environment without traditional management layers.
– Sound technical judgment to establish where AI agent implementation ends and human code review is non-negotiable.

About the customer
Our Customer is building next-generation products for maths learning across both home and school environments. They are developing a greenfield, adaptive learning platform for kids aged 7–12. Built alongside their flagship product, this from-scratch initiative leverages data and AI to personalize study flows, adjust learning speeds, and deliver tailored educational challenges.

Industries
Education