This role requires a highly experienced and versatile individual with a strong technical background in AI/ML and cloud technologies, combined with excellent communication, business development, and Consulting skills. They need to be able to not only design and implement cutting-edge AI solutions but also to engage with clients, identify new opportunities, and drive the adoption of AI within the organization and for its customers. The emphasis on both Google Cloud and AWS suggests a need for multi-cloud expertise.

• AI Solution Design and Implementation: Leading the design and implementation of modern, scalable AI solutions on Google Cloud and AWS, leveraging new and emerging technologies.
• Collaboration: Working closely with cloud consultants, OEM partners, and internal specialists and delivery teams.
• Business Development: Identifying and prioritizing new business opportunities in Applied AI and developing Go-To-Market strategies.
• Solution Architecture: Analyzing, documenting, and optimizing proposed solution architectures, creating SoWs, and building market case studies and use cases.
• Client Engagement: Communicating with clients to understand their requirements and translating them into futuristic AI solutions, guiding them through their AI transformation journeys.
• Thought Leadership: Contributing to the cloud community, creating AI white papers, packaging best practices, and enabling strategic partnerships.
• Technical Expertise: Demonstrating deep expertise in computer vision, NLP, conversational AI, and MLOps, along with a strong understanding of ML architecture and model lifecycle.
• Team Leadership: Aligning, mentoring, and managing teams around strategic initiatives, providing architectural leadership and technical guidance.
• Process & Operations: Establishing processes, operations, measurement, and controls for the end-to-end lifecycle management of intelligent systems.
• Ethical Considerations: (Plus) Familiarity with ethics, regulatory, and compliance factors in data and model management.

Key Skills and Experience:

Is Education overrated? Yes. We believe so. But there's no way we could find you otherwise. So we might look for at least a Master's or MBA degree in Computer Science or engineering field along with:

1. 6-10 years of experience in delivering complex AI projects on Cloud Platform (Google and/or AWS)
2. Cloud Expertise: Strong experience working with Google AI and Data products (BigQuery, Document AI, CCAI, Dialogflow, Vertex AI, Dataprep, etc.) or similar products on other public cloud platforms (AWS is specifically mentioned).
3. AI/ML Architecture: Proven experience in designing and implementing AI/ML solutions, with a deep understanding of ML architecture and the model lifecycle.
4. Applied AI Domains: Demonstrated expertise in computer vision, NLP, conversational AI, and MLOps.
5. Solution Architecture: Solid background in analyzing, documenting, and optimizing solution architectures.
6. Client Communication: Excellent communication and presentation skills to effectively interact with clients and translate their needs into technical solutions.
7. Business Acumen: Ability to identify new business opportunities and contribute to Go-To-Market strategies.
8. Process Management: Ability to establish processes and controls for the lifecycle management of AI systems.

Are you the one? Quick Fit test:

1. Love for technology: When was the last time your dinner entailed an act on “How would ‘Jerry Seinfeld’ pitch AI to this prospect” and your friend did the ‘Sheldon’ version of the same thing.
2. Passion for sales: When was the last time you went at a remote gas station while on vacation, and ended up helping the gas station owner saasify his 7 gas stations across other geographies.
3. Compassion for customers: You listen more than you speak. When you do speak, people feel the need to listen.
4. Humor for life: When was the last time you told a concerned CEO, ‘If Elon Musk can attempt to take humanity to Mars, why can’t we take your business to run on the cloud?’