Enterprise AI Integration Engineer

Enterprise Applications AI Integration Engineer

Job Details:
Level: Experienced,

Job Location:

Penn Center - Denver, CO 80203, Position Type:
Full Time, Salary Range: $ - $ Salary, Job Shift: Day

The Enterprise Application AI Integrations Engineer works in partnership with the AI Architect and Enterprise Applications leadership to implement approved AI solutions and integrations across the organization’s enterprise application environment.

The engineer will work alongside the AI Architect by evaluating technical options, identifying integration requirements, developing proof of concepts, and recommending implementation approaches. The position is expected to provide feedback on architecture patterns and operational controls based on implementation experience.

The role applies hands‑on engineering expertise in intelligent automation, programming, API development, system integration, data mapping and transformation, and cloud and on‑premises application platforms to streamline business processes and enable accurate, consistent data exchange. Working with moderate independence, the engineer translates business and technical requirements into maintainable solutions; supports testing, deployment, monitoring, and production operations; resolves complex issues; and advances platform reliability, security, scalability, and continuous improvement.

The position serves as a technical escalation resource and collaborates with business, technology, security, and vendor partners throughout the application and integration lifecycle.

Ideal Candidate Statement

Takes ownership of commitments, communicates risks early, and follows through on deliverables. Remains effective as priorities, requirements, and technologies evolve. Builds trusted relationships, communicates technical information clearly, shares knowledge, and balances business needs, user experience, security, and operational requirements. Embraces continuous learning and applies sound judgment to emerging technologies, automation opportunities, and AI‑enabled capabilities.

Essential Duties and Responsibilities

• AI Lifecycle Management & Governance:
  Design, implement, and support approved AI‑enabled capabilities, including intelligent automation, virtual agents, and agentic workflows. Apply governance, human oversight, data protection, testing, monitoring, and performance measurement to keep solutions accurate, secure, explainable, maintainable, and aligned with approved business outcomes throughout the lifecycle.
• Automation, AI Enablement & Process Improvement:
  Evaluate business and operational processes to identify and implement approved AI‑enabled, workflow, scripting, integration, and automation solutions. Improve efficiency, consistency, service delivery, data quality, user experience, and risk management, and measure results against defined business outcomes.
• Requirements & Solution Delivery:
  Build trusted partnerships with business, technology, security, and vendor stakeholders. Balance business objectives, user experience, security, maintainability, and organizational standards while coordinating testing, deployment readiness, and transition to support.
• Operational Excellence & Problem Resolution:
  Resolve escalated incidents, diagnose complex production issues, perform root‑cause analysis, and implement corrective actions. Use telemetry and trend analysis to prevent recurrence, reduce technical debt, standardize practices, and improve reliability and operational maturity.
• Documentation & Knowledge Transfer:
  Maintain concise, current, and reusable technical documentation that supports knowledge transfer, operational continuity, audit readiness, recovery, and cross‑functional support.

Other Duties/Responsibilities

• Administer, configure, monitor,…