Founding Data Engineer, AI Platform Onsite (San Francisco, CA)

Dover; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Nth AI is building Nexus, an AI-native implementation platform for trusted data, semantic models, and governed business context. You will design, code, test, and ship the Nexus backend, data integrations, and automation workflows that power enterprise AI implementations.

You’ll work directly with enterprise customers to understand requirements, deploy what you build, and turn challenges into reusable product capabilities that scale across deployments.

Qualifications

• Production software engineering ability: shipped and maintained backend software, APIs, or data infrastructure.
• Deep enterprise data engineering experience: Python, SQL, Spark, data modeling, orchestration, reconciliation.
• Fluency in Microsoft data/AI ecosystem: Microsoft Fabric, Azure AI Foundry, lakehouse, pipelines, semantic models, or agent workflows.
• Enterprise customer experience: work with customer teams and stakeholders to translate needs into working software.
• Strong engineering judgment: verify architecture, code, and data logic using AI tools.

Responsibilities

• Design, code, test, and ship Nexus components including backend services, APIs, and integrations.
• Profile source systems, generate transformations, and build validated lakehouse assets.
• Collaborate with AI engineers to connect agents to data tools and ensure reliable execution.
• Deploy enterprise-ready solutions inside customer environments with proper security and governance.
• Translate customer requirements into reusable product capabilities and integrations.

Skills

Python

SQL

Spark/PySpark

Data modeling

Orchestration

Schema evolution

Reconciliation

Enterprise data engineering

Customer interaction

Engineering judgment

Tools

Microsoft Fabric

Azure AI Foundry

APIs

Backend services

Job description

Build the software that powers enterprise AI implementation.

Nth AI is building Nexus, an AI-native implementation platform that creates the trusted data, semantic models, and governed business context enterprise AI needs to operate.

You will be directly responsible for building Nexus itself: designing, coding, testing, and shipping the software that automates enterprise data integration, transformation, modeling, and validation.

You’ll also work directly with enterprise customers to understand their systems and business requirements, deploy what you build, and turn real implementation challenges into reusable product capabilities.

What you’ll build

• Core Nexus software: Backend services, APIs, integrations, and orchestration workflows that power the product’s end-to-end implementation experience.
• Automated data engineering: Software that profiles source systems, reconciles schemas, generates transformation notebooks and pipelines, and builds validated lakehouse assets.
• Semantic and business context capabilities: Workflows for defining relationships, dimensional models, KPIs, and governed semantic models.
• AI-powered implementation workflows: Partner with our AI engineers to connect agents to data engineering tools, evaluate generated assets, and make execution reliable and inspectable.
• Enterprise-ready deployments: Authentication, permissions, configuration, monitoring, failure recovery, and repeatable deployment inside customer environments.
• Reusable enterprise integrations: Translate customer requirements and complex source-system behavior into capabilities that work across deployments.

What we’re looking for

• Production software engineering ability. You have personally shipped and maintained backend software, APIs, services, or reusable data infrastructure. You can take a capability from design through code review, testing, deployment, and operation.
• Deep enterprise data engineering experience. Strong Python, SQL, Spark/PySpark, data modeling, orchestration, incremental processing, schema evolution, and reconciliation.
• Fluency in the Microsoft data and AI ecosystem. Hands-on experience with Microsoft Fabric and Azure AI Foundry, including relevant lakehouse, pipeline, semantic-model, model-integration, or agent workflows. We also welcome exceptional engineers with substantial experience building comparable enterprise data and AI platforms who can quickly become productive in our stack.
• Enterprise customer experience. You can work directly with customer engineering teams and business stakeholders, navigate complex systems and access requirements, and translate ambiguous needs into working software.
• Strong engineering judgment. You use AI coding tools effectively and can independently verify the architecture, code, and data logic they produce.

Bonus points

Experience integrating legacy ERP systems such as SAP ECC, Oracle E-Business Suite, JD Edwards, PeopleSoft, or Dynamics AX, as well as modern platforms such as SAP S/4HANA and Dynamics 365.

We especially value experience with finance, procurement, inventory, manufacturing, and supply-chain data, including custom schemas, master-data inconsistencies, and reconciliation to business reports.