AI Outcome Customer Engineer IV, Forward Deployed Engineering

Google; Chicago (IL); On-site; USD 233,000 - 324,000; Full time

Job summary

Google is seeking an AI Outcome Customer Engineer IV in Forward Deployed Engineering. The role combines enterprise architecture, technical debugging, and delivery management to shape AI solutions for strategic accounts. You will bridge pre-sales and post-sales work, ensuring adoption and rapid activation within customer ecosystems across multiple U.S.

locations. As a Go-to-Market AI leader, you’ll influence product perspectives, work with deep Google AI capabilities, and translate technical

Qualifications

• Bachelor's degree or equivalent practical experience.
• 10 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.

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.

Skills

Cloud native architecture

Delivery strategies

Reading code

Systems design

APIs & identity

Education

Bachelor's degree or equivalent practical experience

Job description

AI Outcome Customer Engineer IV, Forward Deployed Engineering

Google

New York, NY, USA; Atlanta, GA, USA; +4 more

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.

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.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 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 orchestrating specialized technical resources to execute complex builds.
• Experience diving deep into novel technical problems, deciphering ambiguity, diagnosing bugs, and emerging with credible architectural solutions.
• 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: $233000 - $324000 (USD) + 25% 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 feature requests.
• Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.