Lead Forward Deployed Engineer

Prologis Management; Denver (CO); On-site; USD 150,000 - 190,000; Full time

Job summary

Prologis, a global leader in logistics real estate, seeks a Lead Forward Deployed Engineer to drive AI-infused deployments across core business domains. This senior IC role combines hands-on engineering with strategic delivery, shaping how AI transforms workflows and creates measurable business value within Prologis’ operations.

You will anchor a primary business domain, guide senior FDEs, and establish reusable patterns while collaborating with AI Product, Platform, and Security teams.

Qualifications

• Eight+ years in software/AI engineering and delivery.
• Experience leading complex AI deployments end-to-end.
• Strong Python, APIs, cloud and data platforms.

Responsibilities

• Lead portfolio of deployments across domains and workflows.
• Define outcomes, milestones, production ownership and handoff plans.
• Partner with business leaders to identify high-value AI opportunities and validate value case.
• Ensure production readiness, observability and governance in deployments.

Skills

Python

LLM

APIs

Cloud

Software architecture

Job description

At Prologis, we don't just lead the industry-we define it with a 1.3 billion square foot portfolio and an annual throughput of approximately $3.2 trillion. We create the intelligent infrastructure that powers global commerce, seamlessly connecting the digital and physical worlds. From agile supply chains to energy solutions, our ecosystems help your business move faster, operate smarter and grow sustainably. With unmatched scale, innovation and expertise, Prologis is a category of one-not just shaping the future of logistics but building what comes next. Job Title: Lead Forward Deployed Engineer Company: Prologis

A day in the life

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 our first FDE hire, you will help establish this capability at Prologis and shape how we turn AI into new ways of working and measurable business results. You will be deliberately assigned to a primary Prologis business domain. External hires will generally remain in that anchor domain for 9 to 12 months, and potentially longer, while leading several discrete deployments. This extended assignment allows deep technical expertise to be paired with Prologis operating context and business credibility without creating permanent embedded support. You will structure ambiguous programs, set technical direction, guide Senior FDEs and partner engineers, resolve cross-functional blockers and create patterns that can be reused across Prologis. You will remain accountable for meeting agreed business acceptance criteria and supporting validation through production release, technical stabilization and ownership transfer. This is a senior individual-contributor position and does not require direct people management.

Key responsibilities

• Build deep fluency in an anchor domain and lead a portfolio of deployments spanning multiple workflows, business units or enterprise systems.
• Ensure each deployment has defined outcomes, sponsorship, architecture, milestones, production ownership and a handoff plan.
• Work directly with business leaders, frontline users and AI Product to identify high-value opportunities, understand how work is done today and challenge assumptions about how it could work with AI, informing the value case, success measures and operating constraints for each deployment.
• Translate strategic objectives into redesigned workflows that remove unnecessary steps and handoffs and combine AI agents, software and human judgment effectively; define the technical roadmaps, deployment architectures, dependencies and acceptance criteria needed to deliver them.
• Architect, build, test and troubleshoot production-grade AI applications, agents, retrieval systems, integrations and workflow solutions.
• Set technical direction for FDE deployments and guide implementation across Senior FDEs, central AI engineers and partner teams.
• 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 into the solution.
• Coordinate closely with central AI Product, Applied AI Engineering, Platform, Data and Knowledge, Security and Governance, Process and Agent Orchestration, Enablement, Architecture and AI Operations teams.
• Facilitate business validation against agreed acceptance criteria, resolve technical defects and partner with business owners and Enablement to address adoption barriers and validate workflow improvements during rollout and stabilization.
• Establish production-readiness and handoff criteria, and ensure solutions have durable ownership after deployment.
• Business owners retain accountability for value baselines, adoptio , change management and value realization; the FDE partners with them on process redesign, adoption barriers and validation of workflow improvements.
• Identify patterns that should become shared capabilities, reusable components, evaluation assets or reference architectures.
• Mentor Senior FDEs and raise the quality of technical discovery, engineering, evaluation and stakeholder communication.
• Provide concise executive reporting on value, delivery progress, risks, tradeoffs and decisions.
• Help define the Prologis FDE delivery methodology, engineering standards and engagement playbooks.

How success will be measured

Complex deployments progress beyond demonstrations and pilots into stable production, meet agreed technical, delivery and business acceptance criteria, and demonstrate improvements in how work gets done, validated with business owners against agreed baselines. Multiple workstreams remain aligned and critical dependencies are resolved early. Solutions are secure, reliable, observable, maintainable and supported by clear production ownership. Reusable patterns are scaled through the central AI organization rather than repeatedly rebuilt. Senior FDEs and partner engineers become more effective through technical leadership and coaching. Business and IT leaders have confidence in delivery status, tradeoffs and expected outcomes. The FDE model scales without creating fragmented architecture, unmanaged technical debt or permanent custom-support obligations. Technical leadership is grounded in credible Prologis domain knowledge, hands-on engineering judgment and demonstrated delivery outcomes. Building blocks for success

Building blocks for success

Required Eight or more years of hands-on software engineering, AI engineering, technical delivery or enterprise-solution experience, or equivalent practical experience. Demonstrated success leading multiple complex software or AI deployments from discovery through business acceptance, production release and ownership transfer. Proven experience partnering with business leaders and frontline teams to reimagine an end-to-end business process using AI, personally contributing to the engineering delivery and demonstrating sustained production use and measurable improvements in business outcomes. Strong hands-on programming and architecture skills across Python, APIs, data platforms, cloud and modern application technologies. Deep practical experience with LLM applications, agentic systems, retrieval, tool integration, evaluations, guardrails and production observability. Strong understanding of enterprise architecture, data integration, identity, security, data protection and software-operating models. Ability to lead technical delivery without relying on formal organizational authority. Ability to work directly with senior business executives and translate strategy into executable technical work. Strong 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. Strong written and verbal communication, including executive communication and technical design documentation. Ability to acquire deep domain context quickly and use it to make sound enterprise delivery tradeoffs. A formal engineering or computer-science degree is not required when equivalent practical experience and demonstrated technical leadership are present.

Preferred 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 enterpris