Forward Deployed Engineer, Enterprise AI
Get alerts for roles like this
More Forward Deployed Engineer, Enterprise AI roles in MARINA ONE WEST TOWER, 9 STRAITS VIEW, 018937, Singapore — straight to your inbox. No account needed.
Applying to this role? Tailor your résumé to this job description in one click, then download it clean — no watermark, no subscription.
Job Description
We help global enterprise partners integrate Meta's foundation models and AI tools directly into their core products and infrastructure. We are hiring a Senior Forward Deployed Engineer to independently lead complex technical integrations directly with top enterprise clients.
You will embed closely with external partner engineering teams to deploy, test, and optimize large-scale AI solutions. This is a hands-on role where you will be responsible for ensuring smooth implementations across our platform.
You will tackle ambiguous deployment challenges head-on—like reducing latency, resolving interoperability issues, and building secure data connectors. You will then translate those technical hurdles into actionable feedback, working together with other engineering teams to iterate and refine the AI ecosystem.
If you are a highly skilled engineer passionate about solving complex constraints and driving immediate, measurable impact, we encourage you to apply.
Responsibilities
Own Deployments: Embed directly with client engineering teams to manage the complete deployment lifecycle of AI solutions, from technical scoping to production handoff. Build Integrations & Workflows: Design and implement robust connections between Meta's AI platforms and complex client systems (e. g.
, CRMs, inventory systems, messaging infrastructure), configuring workflows to meet specific partner needs. System Optimization: Architect scalable solutions, analyze code quality, and resolve complex performance and latency bottlenecks in real-world AI workloads.
Develop Reusable Tooling: Act as a force-multiplier by turning one-off deployment patterns into reusable software components and playbooks that accelerate future work.
Implement Evaluation Frameworks: Build and configure rigorous testing frameworks tailored to client environments to ensure AI reliability, safety, and output quality. Provide Technical Leadership: Lead complex technical efforts and cross-functional workstreams while mentoring pee