As an AI Outcome Customer Engineer in Forward Deployed Engineering, you bridge pre-sales and post-sales delivery for strategic AI accounts. You lead enterprise-grade AI design and ensure secure, seamless integration with customers’ data pipelines and identity systems. You diagnose complex implementation issues, coordinate with Product and Engineering to resolve blockers, and guide architectural delivery with cross-functional teams. This role combines technical authority with customer-facing influence to shape adoption and rapid activation across IT ecosystems.
Responsibilities
Partner with account teams and CEs during technical evaluations to assess feasibility, shape proposals for long-term adoption, and validate FDE engagement requests
Lead upfront technical design for enterprise-grade AI solutions, ensuring integration of models, agents, and connectors into customer data pipelines, identity providers, and compliance boundaries
Diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks
Serve as liaison to core Product and Engineering teams, troubleshooting deployment blockers and translating field feedback into actionable feature requests
Steer implementation strategy through technical authority and architectural foresight while owning delivery alongside customer-facing teams
Enter agreement cycle during technical evaluation to ensure solutions are adoption-focused and deliverable
Architect how technical assets integrate into the customer IT ecosystem (connectors, identity, data residency, legal constraints)
Collaborate with cross-functional teams to ensure alignment between pre-sales shaping and post-sales execution
Key requirements
Bachelor’s degree or equivalent practical experience
5 years of experience with cloud native architecture in a customer-facing or support role
Experience with technical delivery strategies and interfacing with product or engineering organizations
Experience in either system design or reading code (e.g., Java, C++, Python)
Experience in system design or orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI)
Experience with enterprise integrations (APIs, enterprise content management (ECMs), identity), Cloud infrastructure, or AI/ML model deployments
diving deep into novel technical problems
exceptional executive communication skills
ability to influence technical stakeholders or executive leaders
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