Remote Senior AI Platform Engineer — Knowledge Graphs & Agents

OpenKrill; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Hire Hangar is seeking a Senior AI Platform Engineer to work remotely with US time zones. You will shape the contextual intelligence layer powering our AI agents, build frontend surfaces for configuration and monitoring, and collaborate across product and data science teams to deliver scalable automated solutions.

The role emphasizes knowledge graphs, RDF/OWL concepts, and modern SaaS engineering practices, with a focus on reliable AI-driven decisions and clear data visualization.

Qualifications

• Senior-level full stack engineering experience.
• Deep understanding of semantic technologies.
• Hands-on experience with AI agent frameworks.
• Strong frontend with React and data viz libraries (D3.js/Recharts).
• Experience with Python backends and ML service integration.
• Experience in fast-moving SaaS environments and remote collaboration.
• Remote-first with asynchronous collaboration.

Responsibilities

• Design and maintain semantic context layers—knowledge graphs, ontologies, and structured context stores.
• 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.

Skills

Full stack engineering

Semantic technologies

Knowledge graphs

React

Python

ML integration

Remote collaboration

Tools

Neo4j

Amazon Neptune

LLM APIs

Agent orchestration frameworks

Job description

Hire Hangar is seeking a Senior AI Platform Engineer to work remotely with US time zones. You will shape the contextual intelligence layer powering our AI agents, build frontend surfaces for configuration and monitoring, and collaborate across product and data science teams to deliver scalable automated solutions.

The role emphasizes knowledge graphs, RDF/OWL concepts, and modern SaaS engineering practices, with a focus on reliable AI-driven decisions and clear data visualization.