Senior AI Deployment Lead

prologis; San Francisco (CA); On-site; USD 200,000 - 285,000; Full time

Job summary

Prologis is seeking a Lead Forward Deployed Engineer to drive enterprise AI deployments, staying hands-on in architecture, code, evaluation and production implementation. You will anchor to a primary business domain and guide senior engineers, defining deployment roadmaps and measurable business outcomes.

You will collaborate with business leaders, AI Product and cross-functional teams to turn strategy into executable technical work, ensuring production readiness and durable ownership across

Qualifications

• 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.

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, adoption, 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.

Skills

Python

APIs

Data platforms

Cloud

LLM apps

Agent systems

Retrieval

Tool integration

Observability

Enterprise architecture

Data security

Data integration

Identity management

CI/CD

Ownership transfer

Tools

AWS

Dataiku

SQL

Automated testing

Containers

CI/CD

Job description

Prologis is seeking a Lead Forward Deployed Engineer to drive enterprise AI deployments, staying hands-on in architecture, code, evaluation and production implementation. You will anchor to a primary business domain and guide senior engineers, defining deployment roadmaps and measurable business outcomes.

You will collaborate with business leaders, AI Product and cross-functional teams to turn strategy into executable technical work, ensuring production readiness and durable ownership across