Hiring mode: W2 contract only
Location: Dearborn, MI
Hybrid Position, 4 days a week onsite. Candidate has to be willing to do an in-person interview. Can submit relocating candidates but they would need to commit to a in-person interview otherwise the manager will not consider them for the role.
Top Requirements:
1. Bachelor Degree is REQUIRED
2. 7+ years of IT experience, 3+ years of software development experience, 2+ years of AI and Graph Engineering experience.
3. Strong Python and Java development skills.
4. Experience with Google Cloud Platform and cloud-native AI/data platforms, Hands-on experience with Vertex AI and BigQuery, Experience with Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, and Cloud Storage.
5. Experience with graph data modeling and querying, including GQL, Neo4j, Spanner Graph, or similar technologies.
6. Experience building LLM/AI agent systems, RAG, grounding, and model integrations.
Required Skills & Experience
- 7+ years of IT experience.
- 3+ years of software development experience.
- 2+ years of AI and Graph Engineering experience.
- Strong Python and Java development skills.
- Experience with Google Cloud Platform and cloud-native AI/data platforms.
- Hands-on experience with Vertex AI and BigQuery.
- Experience with Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, and Cloud Storage.
- Experience with graph data modeling and querying, including GQL, Neo4j, Spanner Graph, or similar technologies.
- Experience building LLM/AI agent systems, RAG, grounding, and model integrations.
- Familiarity with MCP or similar agent tool protocols.
- Experience with MLOps, CI/CD, and production deployments.
- Experience with Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting.
- Experience with Terraform, IAM, security, and secrets management.
- Ability to work with data producers to model and validate enterprise data.
Preferred Experience
- Dataplex or Data Catalog.
- Streaming/CDC and event-driven architectures.
- Event-sourced data modeling.
- User-facing applications and dashboards using Knowledge Graph data.
- Experience with product development, manufacturing, quality, or supply-chain data.
- Data quality frameworks and schema evolution.
- Blue-green or zero-downtime deployments.
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