Forward Deployed Engineer III, GenAI, Google Cloud

Google

San Francisco, CA

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JOB DETAILS

JOB TYPE

Full-time, Employee

SKILLS

Application Programming Interface (API), Artificial Intelligence (AI), Business Strategy, Cloud Computing, Computer Science, Consulting, Cross-Functional, Debugging Skills, Disability Insurance, Embedded Systems, Employee Benefits, Enterprise Architecture, Equal Employment Opportunity (EEO), GCP (Good Clinical Practices), Hardware Design, High Level Architecture (HLA), Information/Data Security (InfoSec), Leadership, Life Insurance, MCP - Microsoft Certified Professional, Mentoring, Metrics, Performance Analysis, Performance Reviews, Problem Solving Skills, Product Planning, Python Programming/Scripting Language, Rapid Prototyping, Return on Investment (ROI), Software Development, Software Engineering, State Laws and Regulations, Structured Data, System Architecture, Systems Scalability, Team Lead/Manager, Team Player, Technical Leadership, Unstructured Data

LOCATION

San Francisco, CA

POSTED

23 days ago

The application window will be open until at least April 23, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.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 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: San Francisco, CA, USA; Boulder, CO, USA; Cambridge, MA, USA; Mountain View, CA, USA; New York, NY, USA; Reston, VA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Los Angeles, CA, USA; Washington D.C., DC, USA; Austin, TX, USA; Chicago, IL, USA; Addison, TX, USA; Detroit, MI, USA; Irvine, CA, USA; Kirkland, WA, USA; Miami, FL, USA; Portland, OR, USA; Atlanta, GA, USA.

Minimum qualifications:

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
6 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.
Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
Experience architecting scalable AI systems on cloud platforms e.g., Google Cloud Platform (GCP).
Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.

Preferred qualifications:

Master’s degree or PhD in AI, Computer Science, or a related technical field.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation.
Knowledge of LLM-native metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

About the job

As a GenAI Forward Deployed Engineer at Google Cloud, you will be an embedded builder bridging the gap between frontier AI products and production-grade reality for our customers. You will function as a builder-consultant, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.This role is designed for high-agency engineers with a founder’s mindset. You will manage blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.

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.

The US base salary range for this full-time position is $153,000-$222,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable return on investment.
Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or product feature requests for the Engineering teams.
Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

About the Company

Google

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