AI Outcome Customer Engineer III, Forward Deployed Engineering

Google•Atlanta, GA

6d•$183,000 - $265,000

About The Position

As an AI Outcome Customer Engineer in Forward Deployed Engineering, you will bridge pre-sales agreement shaping and post-sales execution. Aligned with the Forward Deployed Engineering (FDE) organization, you will steer AI deployments, ensuring solutions are built for long-term viability, rapid activation, and enterprise-grade reliability. You will work with Google Cloud’s Go-To-Market team and use its AI portfolio, including Gemini models and the Vertex AI platform, to help solve customer business problems.

Requirements

Bachelor’s degree or equivalent practical experience.
7 years of experience troubleshooting technical issues for internal or external partners or customers.
Experience in either system design or reading code, such as Java, C++, or Python.

Nice To Haves

Experience with enterprise integrations, including APIs, enterprise content management systems (ECMs), and identity; cloud infrastructure; and AI/ML model deployments.
Ability to conduct in-depth searches into novel technical problems, decipher extreme ambiguity, diagnose bugs, and develop credible architectural solutions.
Excellent executive communication skills, including the ability to translate deep technical integration issues into business impact.

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.
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 definitive 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.