AI Engineer
Core
Design, develop, test, and deploy an AI-queryable knowledge graph and MCP server on Google Cloud Platform to unify industrial data and power engineering, manufacturing, quality, and supply-chain agents.
Role type
Senior IC AI Engineer (Knowledge Graph & Agent Infrastructure)
Builds
A BigQuery property graph and MCP server serving as a tool layer for AI agents.
Domain
Industrial systems, manufacturing, supply chain, and AI infrastructure.
Deliverable
production ML models
Required skills
Java, Python, GCP-native stack (Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Run/GKE), graph data modeling (GQL), LLM/agent systems (tool-use, RAG), observability (SLOs, OpenTelemetry), Infrastructure as Code (Terraform), industrial data modeling.
Preferred skills
Dataplex/Data Catalog, streaming/CDC architectures, user-facing dashboard design, PLM/manufacturing domain knowledge, blue-green deployment strategies.
Technologies
Vertex AI, BigQuery, Dataflow, Apache Beam, Pub/Sub, Cloud Run, GKE, Cloud Storage, Cloud Build, Artifact Registry, Terraform, OpenTelemetry, GQL, Neo4j, Spanner Graph.
Responsibilities
Design and deploy the ISDP knowledge graph from domain event stores to production; model and evolve graph entities and relationships; build and operate the MCP server exposing graph tools to agents; define tool contracts and guardrails for grounded agent responses; own monitoring, observability, and incident response for the graph and MCP layers; partner with data owners to ingest and validate industrial data into ISDP.
Seniority
Senior, hands-on IC
