Senior Founding Engineer (AI)

Location: Hybrid, UK preferred

Company

Building AI-powered business software that automates customer conversations, qualifies leads, converts sales, and helps small-business owners operate and grow through natural-language interaction.

What you will do

• Architect, build, and scale a continuously learning intelligence platform connecting customer interactions, business outcomes, recommendations, and AI evaluation.
• Harden an existing knowledge-layer prototype into a production-ready, scalable, and resilient platform.
• Design event collection architecture and customer interaction pipelines for rich interaction logs.
• Build outcome measurement frameworks that connect AI recommendations to sales, retention, clicks, and other business results.
• Develop recommendation and feedback loops, knowledge graphs, vector databases, memory and retrieval systems, experimentation infrastructure, and feature stores.
• Guide the technical roadmap, establish architectural standards, and protect engineers’ time for focused building while remaining hands-on with production code.

Requirements

• Experience building learning or recommendation systems that measurably improve through real-world feedback.
• Strong systems thinking and experience with distributed systems, event-driven architecture, and large-scale event processing.
• Experience with data engineering, stream processing, feature stores, and robust data modeling.
• Knowledge of graph databases, knowledge graphs, vector databases, retrieval, and memory systems.
• Practical experience with Python, TypeScript, SQL, and modern cloud infrastructure such as AWS, GCP, or Azure.
• Ability to design LLM application architectures and robust AI evaluation frameworks; prior generative AI experience is beneficial but not mandatory.

Culture & Benefits

• Lean, ambitious environment focused on deep building, rapid shipping, and production learning.
• Engineering values include first-principles thinking, intellectual honesty, ownership, and long-term compounding.
• Architecture decisions are debated using data, with flexibility to challenge assumptions and evaluate alternative approaches.
• Work is split between approximately 80% engineering and building and 20% technical leadership and team shielding.
• The role offers ownership of core infrastructure, proprietary learning systems, and the strategic technical direction of the platform.

Hiring process

• Initial conversation about vision, culture, and goals.
• Collaborative architecture design exercise focused on a real learning loop and proving causation for onboarding and retention.
• Technical workshop with the engineering team, followed by a leadership interview and strategy discussion.