应用AI架构师，Meta企业平台

Technical Discovery & Solution Design - Partner with sales to deeply understand customer requirements, business context, and existing technology stacks.

Translate these into clear, technically feasible AI solution architectures and integration plans

Technical Account Ownership - Establish technical account plans covering current use cases, adoption milestones and agreed measures of value.

Review API usage, technical account health and blockers.

Qualify additional use cases and help build the technical case for expansion.

AI Architecture Advisory - Serve as the primary technical advisor throughout the customer's AI / API adoption journey.

Guide architecture decisions around LLM selection, RAG patterns, prompt engineering strategies, agentic workflow and tool use, data pipelines, and enterprise integration points

Evaluation & Proof of Value - Design and guide customer evaluation frameworks (evals) to measure AI performance for specific use cases.

Create compelling demos, reference architectures, and lightweight POCs that demonstrate feasibility and value.

Agree acceptance criteria for quality, latency, cost and reliability, linking evaluation results to customer business goals and a decision on production deployment

Enterprise Trust & Governance - Address enterprise security, compliance, and governance requirements (SOC2, ISO 27001, GDPR).

Navigate complex sales lifecycles involving IT, Legal, Security, and executive stakeholders to build technical confidence

Cross-Functional Collaboration - Act as the bridge between customers and internal Product, Engineering, and PMM teams.

Gather technical feedback, identify common integration patterns, surface product gaps, and contribute field insights that shape the product roadmap and GTM strategy

Thought Leadership & Enablement - Create technical content including architecture guides, best-practice documentation, and industry-specific solution briefs.

Hands-on Solutions - Act as the primary technical owner for strategic accounts.

Assist in the design, prototyping, and deployment planning for customer full-stack applications, RAG pipelines, and custom integrations using our AI APIs.

Rapid Prototyping - Translate customer business problems into concrete technical plans. Rapidly develop and iterate on functional proofs-of-concept (POCs) to demonstrate immediate value

Production Implementation - Guide customers through the "Integration Wall." Navigate enterprise security, legacy databases, and complex infrastructures

Technical Advisory - Serve as a subject matter expert on Generative AI architecture, prompt engineering, model evaluation, and AI security/guardrails for C-level executives and lead developers

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent experience

5+ years of experience in a technical customer-facing role such as AI Architect, Solutions Architect, Sales Engineer, Technical Account Manager, Enterprise Architect or a highly technical Forward Deployed / Solutions Engineering role

Experience engaging enterprise customers through the sales lifecycle, purchasing and deployment decisions, involving multiple stakeholders across IT, Security, Legal, and executive leadership

Experience in consultative selling with a track record of driving technical wins in competitive enterprise sales cycles

Strong understanding of cloud-native architectures (AWS, GCP, or Azure), API design patterns, modern deployment concepts, data integration, identity, security and privacy, and enterprise integration approaches (SSO, data governance, networking)

Comfortable with Python and able to build lightweight demos, scripts, and reference implementations (not expected to write production-grade application code)

Familiarity with the Generative AI ecosystem: APIs, prompt engineering, RAG architectures, vector databases, and evaluation frameworks.

Ability to use LLM APIs to build and evaluate lightweight demos, prototypes and reference implementations

Ability to design use-case-specific evaluation tests and assess quality, latency, cost and reliability against agreed customer requirements and business goals

Experience planning and managing customer technical engagements, resolving blockers and coordinating customer and internal teams through evaluation, integration and adoption.

A high degree of ownership, and the ability to thrive in highly ambiguous, fast-paced environments

Experience communicating complex AI/ML concepts to C-suite executives, IT leaders, engineering teams, and non-technical business leaders while simultaneously working with customer engineering teams

AI/ML solutions at scale in enterprise environments, including model deployment, monitoring, and governance.

Experience helping customers move from evaluation to live applications with measurable business value

Experience creating and delivering technical enablement programs for sales teams, partners, or customer communities

Experience with AI observability, evaluation frameworks (evals) assessing quality, latency, cost and reliability, and implementing enterprise-grade security guardrails for AI applications

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Familiarity with enterprise security and compliance frameworks (SOC 2, ISO 27001, FedRAMP, HIPAA) in the context of AI deployments

Experience with AI safety, responsible AI practices, and implementing guardrails for LLM applications in regulated industries

Hands-on experience building applications using AI APIs (e.g., OpenAI, Anthropic) and familiarity with the Generative AI ecosystem (Vector Databases, RAG architectures, agentic workflows, tool use and frameworks like LangChain/LangGraph)

Meta builds technologies that help people connect, find communities, and grow businesses.

When Facebook launched in 2004, it changed the way people connect.

Apps like Messenger, Instagram and WhatsApp further empowered billions around the world.

Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.

People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

For those who live in or expect to work from California if hired for this position, please click here for additional information.

Individual compensation is determined by skills, qualifications, experience, and location.

Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable.

In addition to base compensation, Meta offers benefits.

Learn more about benefits at Meta.

Meta is proud to be an Equal Employment Opportunity employer.

We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

You may view our Equal Employment Opportunity notice here.

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Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent experience.

5+ years of experience in a technical customer-facing role such as AI Architect, Solutions Architect, Sales Engineer, Technical Account Manager, Enterprise Architect or