Knowledge Engineer — Knowledge Graph & Agentic Interfaces
Core
Build and curate ontology, knowledge graphs, and grounding infrastructure to enable AI agents to understand IFS software and reason accurately over customer data.
Role type
Senior IC Knowledge Engineer (AI Agents & Knowledge Graphs)
Builds
MCP servers, semantic layers, retrieval/grounding infrastructure, skills layers, and control planes for agentic workflows.
Domain
Enterprise software (IFS) + AI/LLM/Agentic systems
Deliverable
production ML models | product features
Required skills
distributed systems, cloud-native architectures, API/schema design, event-driven systems, security, observability, CI/CD, modern backend programming, LLMs, RAG, agentic workflows, orchestration, tool use, function calling, knowledge graphs, semantic modelling, ontology design, embeddings, vector databases, evaluation, benchmarking, prompt engineering, agent tuning
Preferred skills
MCP ecosystems, reusable AI platforms, containerized platforms, hyperscale cloud platforms, reverse-engineering, token-efficient agent design, enterprise software domains
Technologies
RDF/OWL/SKOS, property-graph, vector databases, Docker, Kubernetes, Azure, AWS, GCP, Semantic Kernel, Microsoft Agent Framework, LangGraph, AutoGen, PydanticAI, OpenAI Agents SDK, CrewAI
Responsibilities
Design and build MCP servers over business objects; build write paths for safe agent data modification; design semantic layers with domain experts; build retrieval and grounding infrastructure; establish data quality and versioning practices; build skills layers and control planes; build evaluation harnesses; establish engineering practices; contribute to technical design and mentorship; represent work externally.
Seniority
Senior, hands-on IC