Forward Deployed Engineer IV, GenAI, Google Cloud

Forward Deployed Engineer IV, GenAI, Google Cloud Locations: San Francisco, CA, USA; Boulder, CO, USA; Cambridge, MA, USA; Chicago, IL, USA; Los Angeles, CA, USA; Mountain View, CA, USA; New York, NY, USA; Reston, VA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Washington D.C., DC, USA; Atlanta, GA, USA; Austin, TX, USA; Addison, TX, USA; Detroit, MI, USA; Irvine, CA, USA; Kirkland, WA, USA; Miami, FL, USA; Portland, OR, USA. Benefits 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 per year (increased to 69 hours per 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 Minimum qualifications Bachelor’s degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience. 8 years of experience shipping production-grade AI-driven solutions to external or internal customers. Experience in Python. Experience architecting AI systems on cloud platforms. Experience leading technical discovery sessions with executive stakeholders (C‑suite) and engineering teams to define AI and hardware infrastructure requirements. Experience building full‑stack solutions that interface with enterprise systems. Preferred qualifications Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi‑agent systems using frameworks such as 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. Ability to implement secure agentic workflows incorporating MCP, tool‑calling, and OAuth‑based authentication. About the job As a GenAI Forward Deployed Engineer at Google Cloud, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence products and production‑grade reality within customer environments. Unlike traditional advisory roles, you will function as a builder‑consultant, moving beyond architecture to code, debug, and jointly ship bespoke agentic solutions. This role is designed for high‑agency engineers with a founder’s mindset. You will solve the integration complexities, data readiness, and state‑management issues that prevent AI from reaching enterprise‑grade maturity. By embedding with accounts, you will provide white‑glove deployment and act as a critical feedback loop for Google Cloud’s future product roadmap. 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 US base salary range for this full‑time position is $183,000‑$265,000 plus bonus, equity and 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. Responsibilities Lead the Discovery‑to‑Deployment journey, serving as the lead developer for AI applications and transitioning from rapid prototypes to production‑grade agentic workflows that drive measurable ROI. Bridge the enterprise gap by architecting and coding the connective tissue between Google’s AI products and customer’s live infrastructure, including APIs, legacy data silos and security perimeters. Engineer for production excellence, building high‑performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety and latency. Act as a product catalyst, identifying repeatable field patterns and technical friction points in Google’s AI stack and converting them into reusable modules or product feature requests for the Engineering teams. Drive regional leadership and upskilling by mentoring talent, co‑building with customer teams and influencing cross‑functional strategies to uplevel organizational technical capabilities. Equal Opportunity Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google’s EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire. If you have a need that requires accommodation, please let us know by completing the Accommodations for Applicants form. Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google’s Applicant and Candidate Privacy Policy. #J-18808-Ljbffr Google