Lead Forward Deployed Engineer

Prologis•Denver, CO

About The Position

The Lead FDE partners with business teams to reimagine how work gets done with AI and leads the technical delivery of Prologis’ most complex business-embedded AI deployments while remaining hands-on in architecture, code, evaluation, and production implementation. As the first FDE hire, this role will help establish the FDE capability at Prologis and shape how AI is translated into new ways of working and measurable business results. The Lead FDE will be assigned to a primary Prologis business domain, generally for 9 to 12 months and potentially longer, to build deep operating context while leading several discrete deployments without creating permanent embedded support. This senior individual-contributor role sets technical direction, guides Senior FDEs and partner engineers, resolves cross-functional blockers, and remains accountable through business acceptance, production stabilization, and ownership transfer.

Requirements

Eight or more years of hands-on software engineering, AI engineering, technical delivery, enterprise-solution experience, or equivalent practical experience.
Demonstrated success leading multiple complex software or AI deployments from discovery through business acceptance, production release, stabilization, and ownership transfer.
Proven experience partnering with business leaders and frontline teams to redesign an end-to-end business process using AI while personally contributing to engineering delivery and demonstrating sustained production use and measurable business improvement.
Hands-on programming and architecture capability across Python, APIs, data platforms, cloud, and modern application technologies.
Practical experience building and operating LLM applications, agentic systems, retrieval solutions, tool integrations, evaluations, guardrails, and production observability.
Experience applying enterprise architecture, data integration, identity, security, data protection, and software operating-model requirements to production solutions.
Demonstrated ability to lead technical delivery without formal organizational authority and translate senior business objectives into executable technical work.
Product judgment to distinguish reusable patterns from one-off customization and make disciplined build, buy, or stop decisions.
Demonstrated ability to create reusable engineering components, evaluation assets, standards, and playbooks.
Written and verbal communication skills for executive communication and technical design documentation.
Ability to acquire deep domain context quickly and use it to make enterprise delivery tradeoffs.

Nice To Haves

Experience extending successful AI workflow transformations across business units or geographies within a large global enterprise.
Deep knowledge of one or more Prologis business domains or adjacent industries.
Experience leading several parallel deployments or a portfolio of related AI use cases.
Experience building shared AI components, governed retrieval, knowledge architectures, reference architectures, or enterprise developer tooling.
Experience with AWS, Dataiku, SQL, automated testing, containers, CI/CD, and cloud or hybrid enterprise deployment patterns.
Demonstrates willingness and capability to leverage emerging technology, automation, and AI tools to improve efficiency, quality, and speed.
Exercises sound judgment, creative thinking, and accountability for outcomes.

Responsibilities

Lead a portfolio of AI deployments within an anchor business domain, spanning multiple workflows, business units, or enterprise systems, with defined outcomes, sponsorship, architecture, milestones, production ownership, and handoff plans.
Partner with business leaders, frontline users, and AI Product to identify high-value opportunities, understand current workflows, redesign processes using AI, software, and human judgment, and define value cases, success measures, operating constraints, and acceptance criteria.
Architect, build, test, troubleshoot, and support production-grade AI applications, agents, retrieval systems, integrations, and workflow solutions through release and stabilization.
Set technical direction across FDE deployments, guide Senior FDEs, central AI engineers, and partner teams, and resolve tradeoffs among business value, engineering quality, security, speed, maintainability, and cost.
Design representative test sets, acceptance thresholds, regression testing, observability, security, privacy, auditability, and human controls, and facilitate business validation against agreed acceptance criteria.
Coordinate with AI Product, Applied AI Engineering, Platform, Data and Knowledge, Security and Governance, Process and Agent Orchestration, Enablement, Architecture, and AI Operations to resolve dependencies, support adoption, and establish durable production ownership.
Identify reusable components, evaluation assets, reference architectures, standards, and delivery playbooks; mentor Senior FDEs and partner engineers; and provide concise executive reporting on value, progress, risks, tradeoffs, and decisions.