AI Application Engineer

THE COMPANY:

STACK INFRASTRUCTURE (STACK) provides digital infrastructure to scale the world’s most innovative companies. We are an award-winning industry leader in building, owning, and operating highly efficient, cost-effective wholesale, colocation, and cloud data centers. Each of our national facilities meets or exceeds the highest industry standards in all operational categories of availability, security, connectivity, and physical resilience.

STACK offers the scale and geographic reach that rapidly growing hyperscale and enterprise companies need. The world runs on data. Data runs on STACK.THE POSITION:

We're building enterprise AI platforms that automate document-intensive review workflows across the business. The AI does the heavy lifting on document understanding, rule validation, and exception detection. The Product Engineer builds what users actually see and use — the reviewer workbench, the executive reporting layer, the data products, and the audit-ready outputs that turn AI insights into business decisions.

This is a hybrid product engineering + analytics engineering role. You'll partner with the AI Solution Architect (who owns the agents) and the MLOps Engineer (who owns the data platform) to ship the user-facing layer. You report to the Head of AI & Data Strategy. Responsibilities include but are not limited to:

Reviewer Workbench & application engineering

Reviewer-facing application — triage incoming documents, accept or override AI recommendations, annotate decisionsUI/UX patterns that match how reviewers actually work today (comment logs, page-level evidence links, override flows)
Feedback capture — every reviewer interaction trains the model and refines the rule packs

Application performance at scale — handling high document volumes with thousands of pages of supporting context

Surfacing of agent outputs, confidence scores, and citations to reviewers in a way they trust

Reporting, dashboards & executive visibility

Power BI dashboards on Databricks SQL Warehouse — review throughput, accuracy, time saved, operational metrics

Executive reporting layers for SLT and business leadership

Portfolio analytics — cross-domain benchmarks, trend analysis, anomaly surfacing

Quarterly reporting infrastructure for Steer Co and AI Program Council reviews

Data products & analytics engineering

Clean, documented Gold-layer data products on Unity Catalog — reusable across business stakeholders, IT Delivery, AI team Output generators — auto-produce Excel + Word + linked evidence outputs per reviewed item, audit-ready by defaultAPIs and integration patterns surfacing platform outputs to enterprise systems and business workflows

Analytics engineering standards — dbt or equivalent modeling, version control, lineage, documentation

User research & adoption

Direct work with business users — what's slowing them down, what's working, what they need next

Fast-cadence iteration based on real user feedback, not quarterly release cycles

User documentation, training materials, onboarding flows for end users and report consumers

Cross-functional partnership with the AI Solution Architect, MLOps Engineer, business stakeholders, IT Delivery, SLTTHE DETAILS:

Location:

Denver, COTravel:
Under 10%
Benefits:
Healthcare, Dental Care, Vision Insurance, Life Insurance, Paid Time Off, and Paid Leave Programs Must be eligible to work in the United States Must pass comprehensive background and drug screening MUST-HAVE

QUALIFICATIONS:

5+ years building data-intensive applications, internal tools, or data products in production

Full-stack capability — modern web frameworks (React, Vue, or equivalent), Python or Type Script, SQL Production experience with at least one BI/reporting tool (Power BI preferred)
Strong SQL on Databricks SQL Warehouse, dbt, or equivalent lakehouse modeling

Proven UX intuition — you have shipped internal tools real users adopt and improved them based on observed behavior

Experience designing reporting consumed by executive stakeholders — balancing detail, accuracy, clarity

Microsoft 365 and Azure ecosystem familiarity (Power BI, SharePoint Online, Azure App Services, Entra )Bachelor's degree in Computer Science, Engineering, or…