Senior AI Platform Engineer
At a glance
Senior ML Platform & Ops role at Hire Hangar. Kyiv · contract.
Pay not stated AI Platform Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build semantic context systems, including knowledge graphs and ontologies, to help AI agents interpret and use information
- Create user-facing features for configuring, observing and controlling AI agents
- Connect RPA agents with semantic reasoning so they can automate work using relevant context
- Develop data platform interfaces that show agent activity and data movement in real time
- Turn product and data science requirements into automation, while maintaining engineering quality through tests and documentation
What you bring
- Senior-level experience building full-stack software
- Strong knowledge of semantic technologies such as knowledge graphs, RDF/OWL, ontologies or entity resolution
- Practical experience developing or using AI agent frameworks
- Frontend expertise with React or a comparable framework, plus data visualization tools
- Experience with Python backends and ML service integration, as well as prior remote work and async collaboration
Who this fits
This senior contractor role suits a full-stack engineer who can work across semantic systems, AI agents and user interfaces. It is remote, with work aligned to US time zones from PST through EST. You’ll need previous remote-work experience and the ability to collaborate asynchronously across distributed teams. The application includes a short technical assessment and must be completed in full.
From the employer
Join Hire Hangar and work with fast-growing global companies while building a long-term career.
Job Title Senior AI Platform Engineer
Location Remote
Time Zone US Time Zone (PST - EST)
Role Overview 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
Required 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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