Senior Software Engineer – AI Data & Knowledge Graphs
Hands-on Senior Software Engineer designing knowledge graphs and semantic models using C# and .NET for the Infor MES platform, connecting manufacturing data and IoT sources to enable AI-driven operational intelligence.
- Compensation
- Not disclosed
- Location
- Prague
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Software engineering experience delivering enterprise applications
- C# and .NET development experience
- Enterprise data models and integration solutions
- Graph databases, knowledge graph technologies, or semantic modelling platforms
- APIs and services exposing complex business data
- Integration of multiple enterprise and operational systems
- Relational databases, data modelling, and information architecture
- Cloud-native development and modern SaaS architectures
- Ontology design, semantic modelling, knowledge representation
- Software architecture, scalability, reliability, and observability
- Communication and stakeholder management skills
Nice to have
- Industrial IoT platforms, telemetry systems, or machine connectivity
- Experience in Manufacturing, MES, ERP, or Industrial Automation
- Building semantic models for AI applications
- Vector databases, embeddings, knowledge retrieval
- Event streams, operational data, or real-time telemetry
- OPC UA, MQTT, or industrial integration technologies
- Contributing to technical architecture and engineering standards
- Mentoring engineers or leading technical initiatives
Full description
We are seeking a Senior Software Engineer with expertise in Knowledge Graphs, Semantic Modelling, and Industrial IoT to help establish the connected operational model that underpins next-generation AI capabilities within the Infor MES platform and wider Manufacturing portfolio.
This is a hands-on engineering role focused on connecting manufacturing data, equipment information, production events, and enterprise business context into models that can be effectively understood and leveraged by intelligent systems. You will design and build the relationships, context, and data structures that enable AI solutions to reason across manufacturing operations rather than simply process isolated information.
Working closely with the Principal AI Lead, Product Management, Architecture, and Engineering teams, you will play a key role in enabling AI-driven diagnostics, automation, decision support, and operational intelligence across the Manufacturing portfolio.
As manufacturing software continues to evolve towards AI-driven experiences, this role will help establish one of the most important foundations for future innovation: a connected understanding of manufacturing operations.
- Designing and implementing knowledge graph solutions for manufacturing operations.
- Developing semantic models that represent manufacturing assets, equipment, materials, orders, processes, people, and operational events.
- Integrating MES, IoT, machine, and enterprise data sources into connected operational models.
- Building services and APIs that expose contextual manufacturing information for AI-enabled applications and workflows.
- Working closely with the Principal AI Lead to define ontology strategies, semantic standards, and modelling approaches.
- Designing scalable architectures for ingesting, processing, and modelling industrial IoT and telemetry data.
- Supporting AI reasoning, diagnostics, automation, and decision-support scenarios through rich operational context.
- Developing solutions that support real-time and near real-time operational intelligence initiatives.
- Evaluating emerging technologies in knowledge graphs, semantic modelling, industrial AI, and operational intelligence.
- Contributing to architecture discussions, technical standards, and long-term platform strategy.
- Demonstrated background of software engineering experience delivering enterprise applications or platforms.
- Strong hands-on software development experience using C# and .NET.
- Experience designing and implementing enterprise data models and integration solutions.
- Experience working with graph databases, knowledge graph technologies, or semantic modelling platforms.
- Experience developing APIs and services that expose complex business and operational data.