Senior AI Context Engineer
Core
Designing and implementing enterprise semantic models, certified KPI layers, and AI-safe data abstractions to enable trusted analytics and reliable AI consumption.
Role type
Senior/principal-level cloud data engineer specializing in semantic modeling and AI data platforms
Builds
Enterprise semantic layers, certified KPI frameworks, metadata systems, and AI-ready data abstractions
Domain
Enterprise data platforms, cloud data engineering, AI data infrastructure
Deliverable
production ML models | product features | infrastructure
Required skills
Cloud data engineering, semantic modeling, SQL, Python, dimensional modeling, batch and real-time streaming data systems, metadata management, data quality frameworks, DataOps, Kubernetes, Docker, GCP services (BigQuery, Dataform, Pub/Sub, Composer/Airflow, Cloud Run), open-source tech stack (Iceberg, Trino)
Preferred skills
Data Mesh or domain-driven data architecture, AI/LLM integration patterns including Retrieval-Augmented Generation (RAG), supply chain background
Technologies
GCP (BigQuery, Dataform, Pub/Sub, Composer/Airflow, Cloud Run), Iceberg, Trino, Kubernetes, Docker
Responsibilities
Design and implement enterprise semantic models and certified KPI layers; Build AI-safe data abstraction layers; Develop and enforce data contracts, metadata standards, and semantic governance frameworks; Engineer scalable batch and real-time streaming data pipelines; Collaborate with AI/ML teams to design reliable grounding strategies for AI applications; Implement metadata management capabilities including cataloging, lineage, observability, and automated data quality checks; Apply DataOps principles including CI/CD, automated testing, and deployment automation; Mentor engineers and promote best practices in semantic modeling, governance, and AI-ready platform design
Seniority
Senior, hands-on IC with mentorship responsibilities
