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AI Outcome Engineer, Forward Deployed Engineering

Google · Doha

جديد
Senior 🇬🇧 English
LangGraph AutoGen CrewAI APIs Cloud infrastructure AI/ML model deployments

وصف الوظيفة

About the role

As an AI Outcome Customer Engineer within Forward Deployed Engineering, you bridge the gap between pre-sales agreement shaping and post-sales execution. You enter the agreement cycle during the technical evaluation phase for AI accounts, ensuring solutions are shaped around adoption, rapid activation and viable delivery. You align with the Forward Deployed Engineering organization and architect how technical assets integrate into the customer's IT ecosystem, covering connectors, identity, data residency and legal constraints.

Key responsibilities

  • Partner with Account teams and Practice Customer Engineers during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption and validate FDE engagement requests.
  • Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs and test workarounds to clear execution roadblocks.
  • Serve as the definitive liaison to core Product and Engineering teams, troubleshooting deployment blockers and turning field feedback into actionable feature requests.
  • Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.

Required profile

  • Bachelor's degree or equivalent practical experience.
  • 7 years of experience troubleshooting technical issues for internal or external partners or customers.
  • Fluent speaking and writing in Arabic and English.
  • In-person interviews are required as part of the hiring process.

Required skills

  • Enterprise integrations (APIs, enterprise content management, identity), cloud infrastructure, or AI/ML model deployments.
  • Technical delivery strategies and interface with product or engineering organizations.
  • System design or orchestration frameworks such as LangGraph, AutoGen or CrewAI.
  • Preferred: direct interface with core product or engineering teams on infrastructure or AI/ML deployments, managing technical delivery and debugging systems.

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Doha