As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business challenges, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply your impact and the impact of the team as a whole.
Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You will deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.
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
- Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
- Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
- Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
- Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience with designing cloud-native enterprise-grade technical architecture in customer-facing or support roles.
- Experience building or leveraging AI solutions, ML APIs, prompting, agent tooling, evaluation frameworks, and modern AI frameworks, and embedding into demos.
- Experience with Conversational AI technologies, including designing conversational flows/agents and operating Speech-to-Text, Text-to-Speech (STT/TTS).
- Ability to obtain a Secret security clearance.
Preferred qualifications:
- Experience with building conversational applications and integrating it with third-party tooling (e.g., CRM, ticketing, telephony platforms).
- Experience coding in Java, C++, or Python and vibe coding.
- Familiarity with large language models (LLMs), retrieval-augmented generation (RAG), machine learning templates, and document/image AI.
- Understanding of modern development methodologies and application performance tuning.