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# Principal AI Platform Engineer

- **Company:** Urbane Systems LLC
- **Location:** San Francisco, CA, United States
- **Salary:** $130,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, BigQuery, Information Engineering, Data Systems, Distributed Systems, Graph Database, Python (Programming Language), PostgreSQL, Metadata, OAuth, OpenID, Role-Based Access Control, Standard Sql, Security Assertion Markup Language (SAML), Search Technologies, Single Sign-On, Large Language Models, Snowflake, Apache Spark, Backend, Data Layers, AI Platforms, Data Management, Databricks
- **Published:** July 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c6bd1c1fba4ad863

## About the Role

You are the right fit if you have * Strong experience in data engineering, data platforms, distributed systems, or enterprise data infrastructure. * Practical experience building AI-enabled data systems, retrieval systems, semantic layers, or data agents. * Strong knowledge of SQL, APIs, documents, vector search, knowledge graphs, and metadata systems. * Experience with agentic interfaces, tool-calling, MCP or similar protocols, function calling, or AI backends. * Good understanding of governance: access control, policies, contracts, lineage, data quality, PII protection, and auditability. * Ability to build production systems that are safe, observable, testable, and reliable. * Strong Python skills and comfort working across backend services, data systems, APIs, and AI frameworks. * Product-minded judgment: you know the difference between a demo, a customer-specific workaround, and a reusable platform capability. * Comfort working in ambiguous areas where the patterns are still
being defined.

Nice to have * Experience with data mesh, data products, semantic models, catalogs, governance platforms, or data marketplaces. * Experience with MCP servers, tool registries, LLM orchestration, RAG systems, or multi-step agents. * Experience with Databricks, Snowflake, BigQuery, Spark, DuckDB, Postgres, graph databases, vector databases, or lakehouse architectures. * Experience with enterprise identity and authorization systems such as SSO, OAuth, OIDC, SAML, SCIM, RBAC, ABAC, or policy engines. * Experience evaluating AI systems for retrieval quality, tool-use accuracy, groundedness, reproducibility, and failure modes.



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