Principal AI Platform Engineer

The Principal AI Platform Engineer at Nextdata designs and builds the interfaces systems and agents that make governed enterprise data usable by both humans and AI agents.

The role

The Principal AI Platform Engineer at Nextdata designs and builds the interfaces systems and agents that make governed enterprise data usable by both humans and AI agents.

This role sits at the intersection of data engineering AI engineering distributed systems and product architecture. You will help define how autonomous data products expose their semantics contracts policies metadata and outputs to AI systems through agentic interfaces such as MCP-compatible endpoints typed APIs semantic tools and data agents.

You will not just build pipelines for AI models. You will build the product capabilities that allow AI systems to discover the right data understand its meaning request access execute safe actions and return reliable answers with context lineage and policy enforcement.

• Design agentic data interfaces that let AI agents discover understand and safely use data products.

• Build MCP-compatible endpoints tools and APIs for governed AI/data access.

• Develop data agents that reason over metadata semantics contracts policies and data outputs.

• Make data products AI-ready across SQL documents vectors graphs APIs and semantic models.

• Build safe query and action flows with access checks policy enforcement approvals and audit trails.

• Work on retrieval semantic search tool selection context construction and answer grounding.

• Define reusable patterns for agent-readable metadata structured outputs observability and evaluation.

• Partner with product engineering and customer teams to turn enterprise AI/data use cases into product capabilities.

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.

Required Experience:

Staff IC