AI Platform Engineer — Data Apps, UI & Analytics

STACK Infrastructure US; United States; Hybrid; USD 128,000 - 146,000; Full time

Benefits offered by this job

Healthcare

Dental Care

Vision Insurance

Life Insurance

Paid Time Off

Paid Leave Programs

Job summary

STACK Infrastructure is building enterprise AI platforms that automate document-intensive review workflows. You will implement the user-facing reviewer workbench, data products, and audit-ready outputs that turn AI insights into business decisions.

The role blends product engineering with analytics engineering, partnering with the AI Solution Architect and MLOps Engineer to ship user-centered features and dashboards. Requires strong frontend, backend, and BI experience.

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 — shipped internal tools used by real users.

Responsibilities

• Reviewer Workbench & application engineering.
• Reviewer-facing application — triage incoming documents, accept or override AI recommendations, annotate decisions.
• UI/UX patterns matching reviewer workflows and 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.

Skills

Data-intensive apps

Internal tools

Data products

Full-stack development

Education

Bachelor's degree in Computer Science or Engineering

Tools

Power BI

Databricks SQL Warehouse

dbt

Looker

Job description

STACK Infrastructure is building enterprise AI platforms that automate document-intensive review workflows. You will implement the user-facing reviewer workbench, data products, and audit-ready outputs that turn AI insights into business decisions.

The role blends product engineering with analytics engineering, partnering with the AI Solution Architect and MLOps Engineer to ship user-centered features and dashboards. Requires strong frontend, backend, and BI experience.