1 day ago
London, United KingdomSenior
Responsibilities
- Partner with sales teams to conduct technical discovery and translate customer requirements into feasible AI architectures and integration plans.
- Own technical account plans and advise customers throughout evaluation, deployment, adoption, and expansion.
- Guide architecture decisions involving large language models, retrieval-augmented generation, prompt engineering, agentic workflows, tool use, data pipelines, and enterprise integrations.
- Design evaluation frameworks, demos, proofs of concept, reference architectures, and lightweight prototypes.
- Address enterprise security, compliance, governance, and integration requirements across IT, Legal, Security, and executive stakeholders.
- Bridge customer insights to Product, Engineering, and Product Marketing teams and create technical documentation, solution briefs, training, and reusable assets.
- Support strategic customer deployments from prototyping through production and contribute to organizational strategy, adoption metrics, and peer coaching.
- Travel up to 30% for customer engagements, executive briefings, and field enablement.
Requirements
- 8+ years of experience in a technical customer-facing role such as AI Architect, Solutions Architect, Sales Engineer, Technical Account Manager, Forward Deployed Engineer, or Solutions Engineering.
- Experience engaging enterprise customers through full sales lifecycles and deployment decisions with stakeholders across IT, Security, Legal, executive leadership, and other teams.
- Experience with cloud-native architectures, API design patterns, deployment concepts, data integration, identity, security, privacy, single sign-on, and data governance.
- Experience with Generative AI, APIs, prompt engineering, retrieval-augmented generation architectures, vector databases, and evaluation frameworks.
- Ability to build and assess demos, prototypes, and reference implementations and communicate AI and machine learning concepts to technical and non-technical stakeholders.
- Experience integrating AI tools to optimize or redesign workflows and drive measurable impact.
- Preferred experience with AI observability, quality/latency/cost/reliability evaluation, enterprise security guardrails, responsible AI, and regulated-industry compliance frameworks.
- Preferred experience architecting enterprise AI and machine learning solutions at scale, including deployment, monitoring, governance, and production adoption.
- Hands-on experience building applications with AI APIs and frameworks such as LangChain or LangGraph.
Benefits
- Travel is expected up to 30% of the time for customer engagements, executive briefings, and field enablement activities.
Tech Stack
Categories
Solutions Engineering
About Meta
Meta builds social platforms and communication apps—including Facebook, Instagram, WhatsApp, and Messenger—and develops AR/VR hardware and software such as Quest to power immersive computing. It monetizes primarily through advertising tools for businesses, with additional revenue from devices and services, and operates a massive global infrastructure. Founded in 2004 and headquartered in Menlo Park, California, Meta Platforms, Inc. is a public company traded on Nasdaq under the ticker META.