Forward Deployed Engineer - Contract

Nextdata

United States

On-site

USD 120,000 - 160,000

Full time

14 days+

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Job summary

Nextdata seeks a Forward Deployed Engineer to lead a focused three-to-four-month project with an initial enterprise customer, translating a high-value business need into a production-ready solution on the Nextdata OS.

You will own the project from use-case definition through implementation and deployment, building data pipelines, APIs, and user-facing agentic workflows that consumption of governed data products.

Qualifications

  • Strong experience in data engineering and analytics engineering.
  • Proven ability to own a project from use-case to deployment.
  • Experience delivering data pipelines, APIs, and backend services.
  • Hands-on with enterprise customers and governance-focused data products.

Responsibilities

  • Own project from use-case definition through deployment in production.
  • Build data pipelines, data models, and APIs for enterprise use.
  • Develop user-facing agentic workflows using LangChain/LangGraph.
  • Create MCP-compatible endpoints and semantic interfaces for governed data.
  • Collaborate across data systems, cloud infra, and customer environments.

Skills

Data engineering
Analytics engineering
Python
SQL
Customer-facing delivery
Project ownership
Data governance

Education

Bachelor's degree in a relevant field

Tools

LangChain
LangGraph

Job description

About The Role

As a Forward Deployed Engineer, you will lead a focused three-to-four-month project (which is likely to turn into a longer-term engagement) with one of Nextdata’s initial customers. You will work closely with the customer to translate a high-value business need into a production-ready solution built on the Nextdata OS.

You will own the project from use-case definition through implementation and deployment. This includes data integration, data modeling, pipelines, infrastructure, and the applications through which users and AI agents consume governed data products.

A core part of the project is building a user-facing agentic application, not only the underlying data platform. You will develop workflows that allow users to ask questions, discover and combine relevant data products, invoke tools, and take governed actions. This requires practical experience with LangChain, LangGraph, or similar frameworks for implementing multi-step agent workflows, tool calling, state management, human approval steps, and reliable failure handling.

You will also build the APIs, semantic interfaces, and MCP-compatible endpoints that allow the application and its agents to understand and use enterprise data within defined access and policy controls.

You will draw on experience across the analytics and AI lifecycle, from business requirements and data pipelines to application development and agentic workflows. Lessons from the project will feed back into the Nextdata OS, its developer experience, and reusable product patterns.

The initial engagement is expected to run for three to four months. If successful, the work may expand into a broader product initiative.
What We’re Looking For
  • Strong experience in data engineering, analytics engineering, data platforms, or distributed systems.

  • Experience working directly with enterprise customers and turning business needs into working technical solutions.

  • Ability to own a project from use-case definition through implementation and production deployment.

  • Strong Python and SQL skills, with experience building data pipelines, APIs, and backend services.

  • Practical experience building user-facing agentic applications with LangChain, LangGraph, or similar frameworks.

  • Experience with multi-step workflows, tool calling, state management, RAG, semantic search, and human-in-the-loop approvals.

  • Familiarity with MCP, agent-facing APIs, semantic interfaces, or governed data-access patterns.

  • Understanding of access control, data governance, policies, lineage, PII protection, and auditability.

  • Ability to work across application code, data systems, cloud infrastructure, and customer environments.

  • Strong judgment about scope, trade-offs, and turning a PoC into a reliable product capability.

  • Comfort working in an early-stage environment where requirements may evolve during the project.

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