Senior AI Deployment Architect — Forward-Deployed

Prologis

San Francisco (CA)

On-site

USD 200,000 - 285,000

Full time

4 hours ago
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Job summary

Prologis seeks a Lead Forward Deployed Engineer to drive business-embedded AI deployments. You will lead technically, work directly with business leaders, and guide Senior FDEs, external engineers and partner teams while remaining hands-on in architecture, code, evaluation and production implementation.

You will structure ambiguous programs, set technical direction, and ensure deployments meet acceptance criteria and production readiness.

Qualifications

  • Eight or more years of hands-on software engineering, AI engineering, technical delivery or enterprise-solution 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

  • Lead a portfolio of deployments spanning multiple workflows, business units or enterprise systems and ensure defined outcomes and production ownership.
  • Translate strategic objectives into redesigned workflows that combine AI agents, software and human judgment; define roadmaps and acceptance criteria.
  • 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 and partner teams.
  • Resolve tradeoffs among business value, engineering quality, security, speed, maintainability and cost.
  • Coordinate with cross-functional teams to ensure production readiness and durable ownership after deployment.
  • 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.

Skills

Python
APIs
Data platforms
Cloud
LLM applications
Agentic systems
Retrieval
Tool integration
Production observability
Executive communication

Tools

AWS
Dataiku
SQL
Containers
CI/CD

Job description

Prologis seeks a Lead Forward Deployed Engineer to drive business-embedded AI deployments. You will lead technically, work directly with business leaders, and guide Senior FDEs, external engineers and partner teams while remaining hands-on in architecture, code, evaluation and production implementation.

You will structure ambiguous programs, set technical direction, and ensure deployments meet acceptance criteria and production readiness.

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