Forward Deployed Engineer, Generative AI, Google Cloud
Google · Washington, DC
- On site
- Full-time
- $265,000 / year
- Washington, DC
Job highlights
- Deploy Generative AI solutions for Google Cloud customers.
- Bridge AI products with real-world business challenges.
- Build and deploy end-to-end technical solutions.
- Collaborate with customers and internal teams.
- Drive AI product innovation and strategy.
About the role
About The Job
As a Forward Deployed Engineer, you will play a pivotal role in the Google Cloud AI Go-To-Market organization. You will be focused on frontier AI, including Generative AI (GenAI), in a highly-technical customer-facing role. Your primary responsibility is to bridge the gap between AI products and the customer's real-world business problems.
You will own end-to-end technical delivery, from understanding a client's needs to architecting, building, and deploying solutions directly for or on the customer's infrastructure. Your role requires a blend of deep technical skill, problem-solving, and strong communication with significant customer collaboration and travel often required.
Your primary responsibility will be to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to various clientele ranging from early stage startups to prominent, established companies.
You will be a hybrid professional, blending the core competencies of an engineer with an aptitude for customer engagement and problem-solving. Your role will require you to lead with deep, bespoke implementation as the primary value proposition, ensuring that core technology delivers demonstrable value in the customer's unique operational context. You will have close collaboration with product and engineering teams to eliminate obstacles and shape the future trajectory of offerings. You will be adept at disseminating lessons learned to customers and internal Google teams, translating one-off customer solutions into reusable, scalable assets.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Act as a trusted advisor to customers by understanding their business process and objectives, designing and building end-to-end GenAI-driven solutions spanning AI, Data, and Infrastructure, while partnering with peers to incorporate the full cloud stack into overall architecture.
- Develop production-grade prototypes that deliver measurable outcomes, including writing custom code, integrating disparate data sources, designing data ontologies, deploying solutions on customer infrastructure.
- Represent the customer, gathering real-time feedback and insights, formalizing and abstracting field-tested solutions into reusable modules or new product features to drive product innovation, and establishing technical and business cases to support recommendations.
- Drive cross-functional influence over Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for customer requirements.
- Lead regional field enablement in collaboration with leadership and engage with product and partner organizations on external enablements, with travel as needed.
Key skills/competency
- Generative AI
- Google Cloud
- Python
- Machine Learning
- AI
- Foundation Models
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Client-Facing
- Systems Design
Skills & topics
- Forward Deployed Engineer
- Generative AI
- Google Cloud
- Python
- Machine Learning
- AI Engineer
- Cloud Solutions
- Customer Facing
- Telecommunications
- Foundation Models
How to get hired
- Tailor your resume: Highlight Python, ML, cloud platforms, and client-facing experience. Emphasize Generative AI and foundation model expertise.
- Showcase client-facing success: Detail your experience managing or deploying solutions for telecommunications customers.
- Demonstrate AI/ML proficiency: Provide specific examples of designing, evaluating, or deploying AI systems, especially with foundation models like RAG.
- Prepare for technical deep-dives: Be ready to discuss your experience with architecting, deploying, or managing cloud solutions and distributed training.
- Understand Google Cloud's AI focus: Research their AI strategy, GenAI offerings, and how they serve telecommunications clients.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the minimum qualifications for a Forward Deployed Engineer, Generative AI role at Google Cloud?
- To be considered for this Forward Deployed Engineer, Generative AI role at Google Cloud, candidates need a Bachelor's degree in a STEM field or equivalent practical experience. They must also have 8 years of experience in Python or similar programming languages used in machine learning, a background in client-facing technical roles, experience with applied AI and foundation models (like prompt engineering, fine-tuning, RAG), and experience architecting or deploying solutions on cloud platforms.
- What does a Forward Deployed Engineer do at Google Cloud regarding Generative AI?
- A Forward Deployed Engineer at Google Cloud works in a customer-facing capacity to bridge the gap between AI products, specifically Generative AI, and customer business problems. They are responsible for the end-to-end technical delivery of solutions, from understanding client needs to architecting, building, and deploying these solutions on customer infrastructure, often creating rapid prototypes.
- What kind of experience is preferred for this Generative AI role at Google?
- Preferred qualifications for this role include a Master's degree in a technical field, specific experience delivering AI solutions for telecommunications use cases, experience with distributed training and optimizing performance/costs, experience with large-scale model training and fine-tuning, and strong systems design capabilities. A founder or startup CTO mindset with a bias for action is also valued.
- What is the salary range for a Forward Deployed Engineer at Google Cloud?
- The US base salary range for this full-time position at Google Cloud is $183,000-$265,000 per year. This range does not include potential bonuses, equity, or benefits, which are part of the total compensation package. The specific salary within this range depends on factors like job location, skills, experience, and education.
- Does Google offer remote work for the Forward Deployed Engineer, Generative AI position?
- While the job description mentions preferred working locations in Addison, TX, and Washington D.C., it also states 'By applying to this position you will have an opportunity to share your preferred working location from the following'. This suggests there might be flexibility, but the role inherently involves significant customer collaboration and potentially travel, indicating it may lean towards on-site or hybrid arrangements depending on the specific team and customer needs.
- How does Google Cloud use Generative AI for its clients?
- Google Cloud leverages Generative AI to help organizations digitally transform. For clients, this means building rapid prototype GenAI applications tailored to their needs, addressing specific business problems, and enabling growth. The company aims to deliver enterprise-grade solutions that utilize cutting-edge AI technology to solve critical business challenges.
- What is the role of a Forward Deployed Engineer in driving product innovation at Google?
- Forward Deployed Engineers play a crucial role in product innovation by representing the customer's perspective. They gather real-time feedback and insights from deployments, formalize field-tested solutions into reusable modules or new product features, and advocate for customer requirements to influence Google Cloud's strategy and product direction at the intersection of infrastructure and AI/ML.