AI Outcome Customer Engineer III, Forward Deployed Engineering

AI Outcome Customer EngineerAs an AI Outcome Customer Engineer in Forward Deployed Engineering, you will bridge the gap between pre-sales agreement shaping and post-sales execution. Aligned with our Forward Deployed Engineering (FDE) organization, you will steer AI deployments, ensuring solutions are built for long-term viability, rapid activation, and enterprise-grade reliability.It's an exciting time to join Google Cloud's Go-To-Market team, leading the AI revolution for businesses worldwide. You'll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We'll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We're a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $183000 - $265000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google.In most instances, this position requires in-person interviews as part of the hiring process. Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act. This role may also be located in our Playa Vista, CA campus. Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insurance Retirement Benefits: 401(k) with company match Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA; New York, NY, USA; Los Angeles, CA, USA; Seattle, WA, USA; San Francisco, CA, USA; Sunnyvale, CA, USA.Minimum Qualifications:Bachelor's degree or equivalent practical experience.7 years of experience troubleshooting technical issues for internal/external partners or customers.Experience in either system design or reading code (e.g., Java, C++, Python).Preferred Qualifications:Experience with enterprise integrations (APIs, enterprise content management (ECMs), identity), Cloud infrastructure, and AI/ML model deployments.Ability to do in-depth search into novel technical problems, decipher extreme ambiguity, diagnose bugs, and emerge with credible architectural solutions.Excellent executive communication skills, capable of translating deep technical integration issues into business impact.Responsibilities:Partner with account teams and practice Customer Engineers (CEs) 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.