Vacant job

At Albert Group, we're building next-generation products for maths learning, spanning both school and home. AI is a genuine and relevant part of the solution. It's a from-scratch build alongside Albert Junior, our flagship product, and it's still small enough that the technical decisions you make now will shape how it works for years.

We're looking for a senior engineer to take ownership of our architecture, working across a modern TypeScript stack (backend, web, and mobile) with Python for data processing and analysis of learner signal data. You'll set the standards for how we build — and we mean this seriously: we expect deep, hands-on experience with AI-agentic product development, where AI agents do meaningful parts of the implementation and your job is to direct, review, and hold the bar.

We also put real weight on experience with learner signal engineering and adaptive algorithms — building, analyzing, and tuning the logic that turns raw interaction data into meaningful, personalized behavior. This is one important piece of what makes the product meaningful and personalized for each learner, and getting the parameters and weighting right is one of the more technically interesting problems in the whole system.

What you'll own:

• Core architecture decisions across our product surfaces
• Data pipelines and analytics — including Python-based processing of learner input/output signal data
• Learner signal engineering and adaptive logic — how learner data is captured, analyzed, and tuned to drive what the product does next
• Standards for agentic development across the team: what "good" looks like, and where human judgment is non-negotiable
• Technical direction alongside with full-stack engineers, reporting directly to our COO/CTO

What we're looking for:

• Deep experience architecting modern TypeScript systems at a senior/staff level
• Strong Python skills for data processing/analysis
• Experience with learner signal engineering, adaptive algorithms, or parameter/weighting tuning for personalization
• Real, substantial experience with AI-agentic development workflows — not just occasional use of AI tools, but building this way as a primary mode of work
• Independent, self-directed — flat, no-management-layer team