Founding AI Platform Engineer: Self-Improving Learning

SalesAPE.ai

United Kingdom

Hybrid

GBP 120,000 - 190,000

Full time

14 days+
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Job summary

SalesAPE.ai is seeking a Senior Founding Engineer to build the core, self-improving learning platform behind SalesApe and Self-Serve Abi. You will architect and ship production-grade code, focusing on a scalable, privacy-preserving intelligence layer that learns from millions of business interactions.

You will partner with the Head of Engineering to prioritize the technical roadmap, map data pipelines, and drive end-to-end delivery of learning loops that improve product outcomes over time.

Qualifications

  • Experience in designing and building large-scale learning platforms.
  • Strong background in data engineering, pipelines, and modeling.
  • Proficiency with Python/TypeScript and cloud infrastructure.
  • Knowledge graphs, vector stores, and retrieval systems are a plus.
  • Experience with reinforcement learning or AI evaluation is beneficial.

Responsibilities

  • Architect and build the intelligence layer behind SalesApe and Abi.
  • Lead production-grade, scalable code for a self-improving platform.
  • Collaborate with leadership to prioritize the technical roadmap.
  • Define and maintain robust data pipelines and evaluation frameworks.

Skills

Distributed systems
Event-driven architecture
Data engineering
Stream processing
Feature stores
Data modeling
Graph databases
Vector databases
Python
TypeScript
SQL
Cloud platforms (AWS/GCP/Azure)
Reinforcement learning pipelines
LLM application design
AI evaluation frameworks

Tools

AWS
GCP
Azure
Python
TypeScript
SQL
Knowledge graphs
Vector databases

Job description

SalesAPE.ai is seeking a Senior Founding Engineer to build the core, self-improving learning platform behind SalesApe and Self-Serve Abi. You will architect and ship production-grade code, focusing on a scalable, privacy-preserving intelligence layer that learns from millions of business interactions.

You will partner with the Head of Engineering to prioritize the technical roadmap, map data pipelines, and drive end-to-end delivery of learning loops that improve product outcomes over time.

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