When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. 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 listen and 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.
As a Practice Customer Engineer for Applied AI, you will accelerate Google Cloud’s success by providing technical expertise in Conversational Artificial Intelligence and customer experience. In this role, you will bridge the gap between business issues and highly technical Generative AI solutions. You will partner with Sales teams on high-stakes engagements as a subject matter expert to differentiate Google Cloud, and will be the lead architect for advanced Conversational AI frameworks to design resilient and scalable AI solutions. You will help customers design innovative architectures and solve customer experience issues using first-party Generative AI solutions. You are both a technical expert and a thought leader who will help enterprises navigate Conversational Artificial Intelligence and customer experience from proof-of-concept to production.
In this role, you will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales expertise, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $152000 - $222000 (USD) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build partner specific, go-to-market solutions to reduce business cycles and drive partner business as measured through pipeline and business growth.
- Own the technical relationship with partners, empowering them to drive a successful pilot or proof of concept, support partners drive toward customer acceptance of the technical proposal, leading to an agreement, and work with partners during the migration phase to assure they have all the tools necessary to deliver a successful deployment.
- Build trusted advisory relationships and make recommendations on integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution providing best practice advice to customers to optimize Google Cloud effectiveness.
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 with Conversational AI technologies, including designing conversational flows/agents and operating Speech-to-Text, Text-to-Speech (STT/TTS).
- Experience building or leveraging AI solutions, ML APIs, prompting, agent tooling, eval frameworks, and modern AI frameworks, and embedding into demos.
- Experience engaging with, and presenting to, technical stakeholders and executive leaders.
- 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.