As an AI Outcome Customer Engineer in the go-to-market AI Tech organization, you will bridge the gap between pre-sales agreement shaping and post-sales execution. You will enter the agreement cycle for AI accounts to ensure solutions are shaped through the lens of adoption, rapid activation, and viable delivery, aligning with the Forward Deployed Engineering (FDE) organization. Join Google Cloud’s Go-To-Market team to lead the AI revolution for businesses worldwide, leveraging Google's brand credibility and advanced AI portfolio, including Gemini models and the Vertex AI platform. You will have access to DeepMind's engineering and research minds to help solve customer challenges and drive customer success in the new cloud era.
Tasks
- 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.
- Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
- 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 liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world 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.
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.
- Experience with novel technical problems, deciphering ambiguity, diagnosing bugs, and emerging with credible architectural solutions.
- Experience orchestrating specialized technical resources to execute complex builds.
- Experience engaging with, presenting to, and influencing technical stakeholders or executive leaders.
- Ability to communicate in German fluently to support clients in this region.
- Excellent executive communication skills, capable of translating deep technical integration issues into business impact.
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