Applied AI Architect, Meta Enterprise Platform (London)

Meta; Greater London; Sur place; GBP 120 000 - 180 000; Plein temps

Résumé du poste

Meta is seeking an Applied AI Architect to act as the strategic technical advisor for enterprise customers, guiding them on how to unlock value from Enterprise AI products such as Model API. You will blend Generative AI expertise with enterprise architecture to lead customers from discovery through deployment, adoption, and expansion.

You will own the customer’s technical success, designing scalable architectures, developing reference implementations, and communicating complex concepts to

Qualifications

• 8+ years in a technical customer-facing role.
• Experience with cloud-native architectures and enterprise deployment decisions.
• Ability to design scalable architectures and reference implementations.
• Strong communication with executives, IT and business stakeholders.
• Experience with Generative AI APIs, evaluation frameworks, and governance.

Responsabilités

• Own the customer's technical success from scoping through live production deployment and post-sales adoption.
• Design scalable architectures, reference implementations, and evaluation frameworks.
• Guide customers from discovery to deployment and expansion of Enterprise AI products.
• Champion responsible AI practices, security, and data governance in customer environments.

Connaissances

AI Architecture

Solutions Architecture

Pre-sales Leadership

Executive Communication

Generative AI

AI Observability

Responsible AI

Security & Compliance

LangChain / LangGraph

Outils

AWS

GCP

Azure

Description du poste

As an Applied AI Architect for the Meta Enterprise Platform, you are the strategic technical advisor who helps enterprise customers understand the full potential of our Enterprise AI products (such as Model API) and design the right architectures to unlock that value. You combine deep knowledge of Generative AI with enterprise architecture expertise and effective communication skills to guide customers from initial discovery through successful deployment, ongoing adoption, and expansion. This role combines pre-sales technical leadership with post-sales customer adoption and expansion. You will design scalable architectures, develop evaluation frameworks, create reference implementations, and serve as the technical authority that gives customers and internal stakeholders the confidence to purchase and deploy. You will own the customer's technical success from the initial scoping phase through to live production deployment, post-sales adoption, and growth.

• 8+ years of experience in a technical customer-facing role such as AI Architect, Solutions Architect, Sales Engineer, Technical Account Manager, or a highly technical Forward Deployed or Solutions Engineering role
• Experience engaging enterprise customers through the full sales lifecycle and deployment decisions, involving multiple stakeholders across IT, Security, Legal, and executive leadership
• Experience with cloud-native architectures (AWS, GCP, or Azure), API design patterns, modern deployment concepts, data integration, identity, security and privacy, and enterprise integration approaches such as single sign-on and data governance
• Experience with the Generative AI ecosystem including APIs, prompt engineering, retrieval-augmented generation architectures, vector databases, and evaluation frameworks, with the ability to build and assess lightweight demos, prototypes, and reference implementations
• Experience communicating complex AI and machine learning concepts to executive leaders, IT organizations, engineering teams, and non-technical business stakeholders, and independently navigating decisions involving dependencies across multiple customer and internal teams
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with AI observability, evaluation frameworks assessing quality, latency, cost, and reliability, and implementing enterprise-grade security guardrails and responsible AI practices for large language model applications
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Familiarity with enterprise security and compliance frameworks such as SOC 2, ISO 27001, GDPR, FedRAMP, or HIPAA in the context of AI deployments in regulated industries
• Experience architecting AI and machine learning solutions at scale in enterprise environments, including model deployment, monitoring, governance, and helping customers move from evaluation to live applications with measurable business value
• Hands-on experience building applications using AI APIs and frameworks such as LangChain or LangGraph, and demonstrated ability to integrate AI tools to redesign workflows and drive measurable efficiency or quality improvements