Lead AI Platform Engineer: Scale Enterprise AI

Prologis; Denver (CO); On-site; USD 147,000 - 202,000; Full time

Benefits offered by this job

Healthcare

Dental insurance

Vision insurance

401(k) match

Paid holidays

PTO 22 days

Volunteer time off

Job summary

Prologis is seeking a Lead AI Engineer to build production AI platform capabilities translating building, project and operational data into reusable solutions. You will lead architecture and implementation, partnering with business and security teams to deliver governed AI capabilities across the global real estate portfolio.

The role drives end-to-end AI workflows, including agents, retrieval-augmented generation, and tool calling, with a focus on scalable, observable systems and strong

Qualifications

• 6+ years of software/AI platform experience with end-to-end delivery.
• Experience building AI-powered workflows and agentic systems.
• Ability to translate ambiguous workflows into governed solutions.

Responsibilities

• Design and implement production AI platform capabilities including agents and tool calls.
• Build an AI-native knowledge platform linking models, documents and telemetry.
• Develop multimodal data pipelines from BIM, geospatial and documents.
• Deliver AI workflows for design, construction, operations and sustainment.
• Move prototypes to production with governance, observability and readiness.
• Create reusable engineering patterns to scale pilots into platforms.
• Collaborate with business, tech, security and operations teams.

Skills

Python

TypeScript

JavaScript

APIs integration

Data pipelines

AI platforms

Tools

LangChain

OpenAI API

LlamaIndex

n8n

AutoGen

Job description

Prologis is seeking a Lead AI Engineer to build production AI platform capabilities translating building, project and operational data into reusable solutions. You will lead architecture and implementation, partnering with business and security teams to deliver governed AI capabilities across the global real estate portfolio.

The role drives end-to-end AI workflows, including agents, retrieval-augmented generation, and tool calling, with a focus on scalable, observable systems and strong