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Forward Deployed Engineer

πŸ”₯ 18 hours ago
Enterprise Customer DiscoveryData ArchitectureData WarehousesETL/ELT Pipelines
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πŸ“œ Description

  • Lead customer discovery on data architectures, operating constraints, and deployment requirements.
  • Scope and deliver proofs of value from technical validation through production commitments.
  • Demonstrate products, address technical objections, and discuss architecture with enterprise stakeholders.
  • Create repeatable discovery, demo, objection-handling, and reference-architecture materials.
  • Translate customer edge cases and constraints into actionable product feedback.
  • Partner with machine learning and infrastructure teams to deliver customer-aligned deployments.

πŸ› οΈ Requirements

  • At least 5 years of professional experience, including 2 to 3 years in hands-on engineering or data work.
  • A record of personally converting enterprise B2B software proofs of value into production commitments, including experience with procurement, security reviews, and multi-stakeholder buying processes.
  • Strong knowledge of data warehouses, ETL or ELT pipelines, and data governance in enterprise environments.
  • Experience leading technical discovery and demos with enterprise stakeholders, and delivering proofs of concept through production deployment.
  • Working knowledge of production LLM and agentic systems, including their current capabilities and limitations.
  • Ability to prototype with Python or SQL and communicate customer needs clearly to engineering teams.
  • Experience with knowledge graphs, semantic layers, ontologies, entity resolution, regulated or air-gapped deployments, or multiple European markets is valuable.
  • Comfort with ambiguity and startup environments; multilingual ability is a plus.
Full job description

About the Role

Join an early-stage enterprise AI infrastructure team as its technical lead for customer engagements across the UK and Europe. You will connect customer needs with product and engineering, guiding enterprise deployments of AI systems that depend on reliable, governed business data.

What You'll Do

  • Lead customer discovery to understand data architectures, operating constraints, and deployment requirements.

  • Scope and deliver proofs of value from technical validation through production commitments.

  • Run product demonstrations, address technical objections, and discuss architecture with senior engineering and business stakeholders.

  • Develop repeatable materials and approaches for discovery, demonstrations, objection handling, and reference architectures.

  • Turn customer edge cases and technical constraints into actionable product feedback for engineering.

  • Partner with machine learning and infrastructure teams to deliver deployments aligned with customer requirements.

  • Travel regularly to customer sites across the UK and Europe.

What We're Looking For

  • At least 5 years of professional experience, including 2 to 3 years in hands-on engineering or data work.

  • A record of personally converting enterprise B2B software proofs of value into production commitments, including experience with procurement, security reviews, and multi-stakeholder buying processes.

  • Strong knowledge of data warehouses, ETL or ELT pipelines, and data governance in enterprise environments.

  • Experience leading technical discovery and demos with enterprise stakeholders, and delivering proofs of concept through production deployment.

  • Working knowledge of production LLM and agentic systems, including their current capabilities and limitations.

  • Ability to prototype with Python or SQL and communicate customer needs clearly to engineering teams.

  • Experience with knowledge graphs, semantic layers, ontologies, entity resolution, regulated or air-gapped deployments, or multiple European markets is valuable.

  • Comfort with ambiguity and startup environments; multilingual ability is a plus.

Location

Hybrid, based in New York, United States, with regular travel to customer sites across the UK and Europe.

Own customer deployments from requirements through reliable production implementation, building AI workflows and integrations, resolving live issues, and turning recurring customer needs into product improvements.

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