AI Outcome Customer Engineer II, Forward Deployed Engineering

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.

This role may also be located in our Playa Vista, CA campus.

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.

In most instances, this position requires in-person interviews as part of the hiring process.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Austin, TX, USA; Chicago, IL, USA; Los Angeles, CA, USA; Sunnyvale, CA, USA; San Francisco, CA, USA.

Minimum qualifications:

• 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.

Preferred qualifications:

• Experience diving deep into 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.
• Excellent executive communication skills, capable of translating deep technical integration issues into business impact.

About the job

As an AI Outcome Customer Engineer in our go-to-market (GTM) AI Tech organization, you will work as an enterprise architect, technical debugger, engineering liaison and technical delivery manager. You will bridge the gap between pre-sales agreement shaping and post-sales execution. Entering the agreement cycle during the technical evaluation phase for strategic AI accounts, you will ensure that solutions are shaped strictly through the lens of adoption, rapid activation, and viable delivery. Aligned with our Forward Deployed Engineering (FDE) organization, you will architect how these technical assets actually integrate into the customer’s IT ecosystem (connectors, identity, data residency, legal constraints).

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: $152000 - $221000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

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 …