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# Senior AI Platform Engineer

- **Company:** The Hire
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software as a Service, Databases, D3.Js, Data Visualization, Graph Database, Python (Programming Language), Knowledge Management, Neo4j, Named Entity Recognition, Node.Js, Open Source Technology, Data Streaming, TypeScript, ReactJS, Large Language Models, Agentic-AI, AI Platforms, Slack, Gsuite, Front End Software Development, Virtual Agents, Entity Resolution
- **Published:** November 5, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pwofvodij6

## About the Role

* Senior-level full stack engineering experience
 * Deep understanding of semantic technologies - knowledge graphs, RDF/OWL, ontologies, or entity resolution
 * Hands-on experience building or consuming AI agent frameworks
 * Strong frontend skills with React or similar, including data visualisation libraries such as D3.js or Recharts
 * Experience with Python-based backends and ML service integration
 * Comfort working in fast-moving SaaS product environments
 * Must have prior remote work experience and demonstrated ability to collaborate asynchronously across distributed teams

Preferred Qualifications

 * Experience with graph databases such as Neo4j or Amazon Neptune
 * Exposure to NLP pipelines and named entity recognition (NER)
 * Contributions to open-source AI or semantic tooling
 * Experience with enterprise-scale knowledge management systems

Tools & Technology

 * Python / Node.js
 * React / TypeScript
 * Graph or semantic databases (Neo4j, Amazon Neptune, or similar)
 * LLM APIs and agent orchestration frameworks
 * Data visualisation tooling (D3.js, Recharts, or similar)
 * Slack, Zoom, Google Workspace

## Description

You will work at the cutting edge of how structured knowledge is used to make AI agents smarter and more reliable. This is a role for an engineer who thinks deeply about context, meaning, and how machines can be equipped to make better decisions - and who can also build the frontend surfaces that make those capabilities accessible to end users., * Design and maintain semantic context layers - knowledge graphs, ontologies, and structured context stores - that inform agent behaviour

 * Develop full stack features that allow users to configure, monitor, and control AI agents through intuitive interfaces
 * Integrate RPA agents with semantic reasoning capabilities, enabling context-aware automation at scale
 * Build and maintain data platform frontends that provide real-time visibility into agent activity and data flows
 * Work closely with product and data science teams to translate business requirements into intelligent automation solutions
 * Champion engineering quality through testing, documentation, and architectural consistency