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STACK Infrastructure

engineering opportunity

AI Application Engineer

The AI Application Engineer will build enterprise AI platforms and user-facing reviewer workbenches to automate document-intensive workflows. Responsibilities include developing analytics dashboards, managing data products, and collaborating with AI architects to refine model performance based on user feedback.

Denver, Colorado, United StateshybridFULL_TIME

Posted

About the role

What will you do at STACK Infrastructure?

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 decisions
  • UI/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 SteerCo 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 default
  • APIs 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, SLT
  • THE DETAILS:
  • Location: Denver, CO
  • Travel: 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 TypeScript, 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 ID)

Bachelor's degree in Computer Science, Engineering, or related field

Nice to have

Power BI Data Analyst Associate or Databricks Data Analyst Associate certifications

Document-heavy UX experience — PDF viewers, annotation tools, evidence linking, comment logs

Experience surfacing LLM outputs to end users — confidence scoring, override flows, citation interfaces

React + TypeScript + modern frontend tooling and component libraries

Embedded analytics (Power BI embedded, Looker embedded, or equivalent)

Construction, real estate, data center, or AEC industry context

Experience operating in a small AI team where you wear multiple hats

How you work

You build for the user in front of you. You would rather watch a user use what you built than read about adoption metrics.

You're comfortable with ambiguity. You figure out what the user needs by talking to them, not by waiting for a spec.

You ship small and often. Big quarterly releases are not your model.

You think about data products as products. A Gold-layer table should be documented, versioned, and reliable.

Compensation

Range:

$128,260.00 - $146,017.59

THIS MIGHT BE RIGHT FOR YOU IF:

You are a strong communicator, you are persuasive and clear, blending analytics with experience in decision-making.

You do not get flustered easily. You can juggle multiple priorities while balancing urgent requests with shifting timelines and deliverables.

You are a team builder. You take the time to understand and develop the strengths of your resources while formulating long-term plans for the growth and success of the team.

You are naturally curious and driven toward continual improvement. While you celebrate your successes, you take time to review and analyze campaigns for future learning.

WHY STACK?

We offer a competitive compensation package with strong benefits, including medical, dental, and vision insurance, a 401K program, flexible spending accounts – even a cell phone subsidy.

We foster a culture of appreciation, including peer-to-peer recognition and rewards programs.

Fun is part of our DNA, with events, game nights, happy hours, and barbecues.

We’re growing – this is a great time to join and make an impact!

STACK is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity and expression, age, national origin, mental or physical disability, genetic information, veteran status, or any other status protected by federal, state, or local law

Note to external agencies: We are not accepting any blind submissions or resumes/cvs from recruitment agencies. Any candidates sent to STACK Infrastructure, Inc. will not be accepted or considered as a submission without a signed agreement in place. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of STACK Infrastructure, Inc.

Which skills does this role require?

PythonVueData EngineeringAnalytics EngineeringUI/UX DesignAPI IntegrationMachine Learning OperationsData ModelingAI Application EngineerData InfrastructureMachine LearningUnity CatalogFull-stack DevelopmentData ProductsWorkflow AutomationDocument UnderstandingVersion ControlLineageAPICloud Data CentersWholesale ColocationHyperscaleEnterprise AIModel TrainingFeedback LoopsAnomaly DetectionPortfolio AnalyticsVue.jsLLMsUser Research

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