Senior AI Platform Engineer
Nextdata
Senior AI Platform Engineer
Nextdata
Data mesh platform with federated governance
Quickly understand the existing codebase, requirements, and technical direction.
Build backend services, AI agents, tools, and APIs for governed data access.
Implement MCP-compatible endpoints or similar agent interfaces.
Integrate SQL, documents, APIs, metadata, semantic models, and vector search.
Build retrieval, tool selection, context construction, and grounded response flows.
Add access controls, policy enforcement, audit logging, tests, and observability.
Deliver a reliable, documented system within the three-month project scope.
Strong experience with backend systems, data platforms, or distributed systems.
Practical experience building agentic AI applications using LangChain, LangGraph, or similar frameworks.
Experience with RAG, retrieval, semantic search, tool calling, and multi-step agent workflows.
Strong Python and API development skills.
Experience with SQL, documents, metadata systems, and vector search.
Familiarity with MCP or similar agent interfaces.
Understanding of access control, policies, lineage, data quality, PII protection, and auditability.
Ability to become productive quickly in an unfamiliar codebase.
Good judgment on scope, trade-offs, and production readiness.
Experience with data products, data mesh, semantic models, catalogs, or governance platforms.
Experience with MCP servers, tool registries, or multi-step agents.
Experience with Databricks, Snowflake, BigQuery, Spark, DuckDB, Postgres, graph databases, or vector databases.
Familiarity with OAuth, OIDC, SAML, SSO, RBAC, ABAC, SCIM, or policy engines.
Experience evaluating retrieval quality, tool accuracy, groundedness, and failure modes.
Initial term: three to four months.
Focus: hands-on implementation and delivery.
No customer-facing responsibilities.
Potential extension if the project is successful.
Nextdata provides Nextdata OS, a data mesh–native platform that makes data management manageable for large organizations by treating data as a product. It uses autonomous, containerized data products that bundle data, code, metadata, and governance policies, running across multiple clouds and infrastructures to automate governance, orchestration, security, and discovery. Unlike traditional centralized data lakes or catalogs, Nextdata emphasizes domain-owned, self-governing data products and federated governance to enable seamless data sharing and interoperability. The goal is to accelerate value from data by delivering scalable, governed, and shareable data assets that power analytics and AI across business units.
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