Join a small enterprise AI infrastructure team as its technical front line for customer engagements across the UK and Europe. You will connect customer needs with product and engineering work, guiding technical evaluations through deployment while helping establish the team's field playbook.
Lead customer discovery to understand data architectures, operational constraints, and opportunities for AI agents.
Scope and deliver proofs of value from initial requirements through technical validation and production deployment.
Run demonstrations, address technical objections, and discuss architecture with senior engineering and business stakeholders.
Conduct technical deep-dives with data platform, infrastructure, and executive teams across European markets.
Develop reusable discovery frameworks, demo narratives, objection handling, and reference architectures.
Translate customer edge cases and requirements into actionable feedback for product and engineering teams.
Partner with machine learning and infrastructure teams to deliver deployments that meet customer expectations.
At least 5 years of professional experience, including 2 to 3 years in hands-on technical or data roles building systems.
A record of converting technical proofs of value into production commitments in enterprise B2B software.
Strong knowledge of data warehouses, ETL/ELT pipelines, data governance, and enterprise data architectures.
Experience with enterprise discovery, technical demos, security reviews, procurement, and multi-stakeholder buying processes.
Working knowledge of production LLM and agentic systems, including their capabilities and limitations.
Ability to use Python or SQL for customer-facing prototyping and to turn technical findings into structured engineering feedback.
Willingness to travel regularly to customer sites across the UK and Europe.
Experience with knowledge graphs, semantic layers, ontologies, entity resolution, or regulated and air-gapped deployments is valuable. Multilingual ability, European market experience, and startup experience are also beneficial.
Visa sponsorship is not available.
Hybrid, New York, United States. The role includes regular travel to customer sites across the UK and Europe.
Build and deploy production-grade, LLM-enabled applications with strategic customers, owning full-stack implementation, AI orchestration, and reusable engineering patterns that scale across enterprise deployments.
Build and deploy production-grade, LLM-enabled applications with strategic customers, owning full-stack implementation while creating reusable AI patterns and influencing platform tools and product direction.
Own end-to-end delivery of production-grade, LLM-enabled applications, partnering with customers to architect and deploy AI solutions while creating reusable tools and patterns that scale across enterprise deployments.
Own enterprise customer deployments of AI agents from onboarding through production, building integrations, tuning LLM workflows, and translating customer needs into product and engineering improvements.
Lead customer deployments of voice AI from requirements through production, building integrations and reliable workflows while using deployment insights to improve the product.
