N
Nextdatavia Ashby
Senior AI Platform Engineer Contract
San Francisco, CAPosted 6d ago
OtherSeniorFull-time
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About the Role
NEXTDATA IS LOOKING FOR AN EXPERIENCED AI PLATFORM ENGINEER FOR AN INITIAL THREE-MONTH PROJECT FOCUSED ON BUILDING AND VALIDATING AN AI-ENABLED DATA PLATFORM CAPABILITY.
THIS IS A HANDS-ON IMPLEMENTATION ROLE. YOU WILL QUICKLY RAMP UP ON AN EXISTING PROJECT AND BUILD BACKEND SERVICES, AGENT TOOLS, APIS, AND DATA INTEGRATIONS. THE ROLE HAS NO CUSTOMER-FACING RESPONSIBILITIES AND LESS EMPHASIS ON ARCHITECTURE THAN A PRINCIPAL-LEVEL POSITION.
IF SUCCESSFUL, THE PROJECT MAY CONTINUE AND DEVELOP INTO A BROADER NEXTDATA PRODUCT.
WHAT YOU’LL DO
- 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.
-
WHAT WE’RE LOOKING FOR
- 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.
NICE TO HAVE
- 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.
CONTRACT SCOPE
- Initial term: three to four months.
- Focus: hands-on implementation and delivery.
- No customer-facing responsibilities.
- Potential extension if the project is successful.
THIS IS A HANDS-ON IMPLEMENTATION ROLE. YOU WILL QUICKLY RAMP UP ON AN EXISTING PROJECT AND BUILD BACKEND SERVICES, AGENT TOOLS, APIS, AND DATA INTEGRATIONS. THE ROLE HAS NO CUSTOMER-FACING RESPONSIBILITIES AND LESS EMPHASIS ON ARCHITECTURE THAN A PRINCIPAL-LEVEL POSITION.
IF SUCCESSFUL, THE PROJECT MAY CONTINUE AND DEVELOP INTO A BROADER NEXTDATA PRODUCT.
WHAT YOU’LL DO
- 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.
-
WHAT WE’RE LOOKING FOR
- 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.
NICE TO HAVE
- 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.
CONTRACT SCOPE
- Initial term: three to four months.
- Focus: hands-on implementation and delivery.
- No customer-facing responsibilities.
- Potential extension if the project is successful.
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