Senior AI & Data Engineer (Azure Databricks, Microsoft Fabric & Microsoft Foundry)

Pay $145,000 to $185,000 per year. Full-time, remote (US).

About ArchitectNow

For 18 years, ArchitectNow has helped businesses ship software that does the work. We are a Microsoft Solutions Partner with active designations in Digital & App Innovation (Azure), Data & AI (Azure), and Infrastructure (Azure). Across cloud-native applications, data platforms, AI, the Power Platform, and the managed cloud services that keep production running, our focus has always been getting hard things built, well, and on time.

What has changed is how we build them. We are in the middle of a fast, deliberate move into an AI-first practice. Our engineers use Claude, GitHub Copilot, and a growing stack of internal AI tooling to put their experience to work on harder problems and ship faster than the industry standard.

We are fully remote across 14 states. We are small enough that your work is visible to leadership the same week you do it, and there are no layers between an engineer and the client by design.

The role

Our clients have stopped asking whether they should use AI. They are asking why their numbers don’t match, why their data isn’t ready for Copilot, and how to get an agent into production without putting protected data at risk. Those are data problems first and AI problems second. This role exists to solve both.

The Senior AI & Data Engineer is a new role at ArchitectNow. You will be the technical lead on our Azure data and AI engagements, running discovery and solution design, then building the platform alongside one of our agile delivery teams. Depending on the client, that platform may be Microsoft Fabric, end-to-end Azure Databricks, or Azure Data Factory with Azure SQL. Our current work includes consolidating a health system’s departmental databases into a governed Microsoft Fabric warehouse with a certified Direct Lake model and a data agent for leadership, and standing up Microsoft Fabric and Microsoft Foundry across four environments for a national insurer, including RAG over millions of claims documents and a production intake automation workload.

These are joint builds. Client data teams work alongside us, and every engagement ends with them able to run and extend what we built. Teaching is part of the job.

What you will actually do

You will lead the technical side of data and AI engagements from discovery through production handover. You will sit on a delivery team with a Delivery Lead and developers, doing time-and-materials project work across one or two clients at a time.

A typical week. Monday you are in a discovery session with a client’s analytics director, mapping where their metric definitions diverge and which tables need change data capture before replication will work. Tuesday you are in a notebook moving business logic upstream into the Gold layer so the semantic model stays simple and fast. Wednesday you are tuning a data agent’s grounding instructions against a set of known business questions and writing down where it still gets things wrong. Thursday you are reviewing a teammate’s pipeline PR and walking the client’s new data engineer through your medallion conventions. Friday you are helping our sales team scope the next engagement.

Specifically, you will

• Lead discovery and solution design for Azure data and AI engagements, and turn findings into architecture, phased plans, and estimates our team can deliver against
• Lead technical execution on AI and data engagements, guiding the delivery team through planning, build, and handover to successful delivery
• Design and build lakehouse and warehouse platforms on Microsoft Fabric, Azure Databricks, or Azure Data Factory with Azure SQL, including ingestion, medallion architecture, pipelines, notebooks, and certified semantic models
• Build production AI solutions on Microsoft Foundry, Azure AI Search, and a range of foundation models, including RAG, document processing, evaluation, content safety, and human-in-the-loop review
• Ground Microsoft Copilot, Copilot Studio agents, and data agents on governed enterprise data
• Implement security and governance that holds up in regulated environments, including Entra groups, row- and object-level security, Purview, private networking, and PHI controls
• Set up CI/CD and environment promotion for data and AI workloads
• Reconcile, validate, and cut over from legacy systems
• Write the documentation, runbooks, and reusable patterns that let clients and our own team repeat …