Senior AI Platform Engineer
Hire Hangar
Role Description
This role sits at the intersection of AI engineering and platform development. As a Senior AI Platform Engineer, you will own the contextual intelligence layer that powers our AI agents — ensuring they understand, reason, and act with precision across our SaaS ecosystem.
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.
Key Responsibilities
- 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.
Qualifications
- 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
Please Note
It is crucial that you complete the application form in full. As part of the application process, you will be required to complete a short technical assessment. If your application is successful, you will receive an email confirming next steps. Applications that are not completed in full will not be considered for any open roles.
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