Forward Deployed Engineer, Enterprise AI

Meta•Seattle, WA

4d•$183,997 - $257,000

About The Position

Meta is hiring an experienced Staff Forward Deployed Engineer to act as the primary technical bridge between its internal engineering teams and enterprise clients. The role leads the architecture and rollout of large-scale AI systems, working with partner engineering leaders to adapt Meta’s AI platform to their environments and constraints. The engineer will address deployment challenges such as inference speed, interoperability, and external data integration, then turn field experience into technical proposals that inform the roadmap for Meta’s AI tools and ecosystem.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.
Demonstrated experience driving organizational change and leading complex technical projects.
8+ years of programming experience in a relevant language, or 4+ years of experience with a PhD.

Nice To Haves

Experience architecting and deploying large-scale software systems, including taking complex AI applications from prototypes to enterprise-ready production.
Experience architecting and scaling GenAI infrastructure across major cloud platforms such as AWS or GCP, using cloud compute, distributed storage, and ML frameworks to optimize model performance, manage compute costs, and ensure enterprise-grade reliability.
Experience designing and implementing advanced AI testing systems, such as automated evaluation loops to detect hallucinations, reasoning gaps, or safety issues in live products.
Experience in regulated industries such as financial services, insurance, or healthcare, or experience navigating enterprise compliance requirements such as SOC2, data residency, and privacy frameworks.
Ability to lead technical engagements with external engineering teams and translate complex business constraints into robust system designs.
Ability to bridge field deployments and internal engineering, using hands-on customer insights to shape product and platform roadmaps.
Ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Ongoing AI skill development, including prompt or context engineering and agent orchestration, and keeping current with emerging AI technologies.

Responsibilities

Lead technical design for major enterprise AI deployments, ensuring scalability, security, and compliance with partner requirements.
Design reliable integrations between Meta AI platforms and client infrastructure, including CRMs, data warehouses, and custom APIs.
Connect field deployments with internal platform teams and translate real-world challenges into strategic product decisions.
Define deployment patterns, build tooling, and establish engineering standards to reduce technical debt and accelerate future execution.
Set technical direction, drive cross-functional initiatives, mentor team members, and guide new engineers.
Identify and resolve performance, latency, and scalability bottlenecks in live production environments.