Applied Solutions Architect, Google Cloud

Responsibilities

• Lead the technical discovery sessions to understand customer requirements and their current technology landscape. Design comprehensive system architectures and run iterative workshops with stakeholders to lock in project scope, always architecting with the final end-state in mind.
• Move seamlessly from high-level architecture to low-level implementation. Code, build, and deploy robust cloud systems, ensuring technical designs translate into functional, integrated realities.
• Architect and engineer enterprise-grade AI solutions—such as agentic workflows, RAG systems, and applied foundation models—backed by highly scalable, cloud-native infrastructure including event-driven microservices, containerized workloads, and serverless compute.
• Engineer functional PoV products that integrate into the customer's as-is systems to demonstrate true business value. Ensure all builds adhere strictly to engineering best practices, security standards, and scalability guidelines to ensure a smooth transition to production.
• - Lead the technical discovery sessions to understand customer requirements and their current technology landscape. Design comprehensive system architectures and run iterative workshops with stakeholders to lock in project scope, always architecting with the final end-state in mind. - Move seamlessly from high-level architecture to low-level implementation. Code, build, and deploy robust cloud systems, ensuring technical designs translate into functional, integrated realities. - Architect and engineer enterprise-grade AI solutions—such as agentic workflows, RAG systems, and applied foundation models—backed by highly scalable, cloud-native infrastructure including event-driven microservices, containerized workloads, and serverless compute. - Engineer functional PoV products that integrate into the customer's as-is systems to demonstrate true business value. Ensure all builds adhere strictly to engineering best practices, security standards, and scalability guidelines to ensure a smooth transition to production.

Minimum qualifications:

Preferred qualifications:

Qualifications

• Minimum qualifications: - Bachelor's degree in a technical field or equivalent practical experience. - 6 years of experience with cloud native architecture in a customer-facing or support role. - Experience architecting AI systems on cloud platforms. - Experience building full-stack solutions that interface with enterprise systems. - Experience engaging with, or presenting to, technical stakeholders or executive leaders. Preferred qualifications: - 4 years of experience in software development, systems architecture, or a highly technical customer-facing role with proficiency in one of more general-purpose programming languages (e.g., Python, Java, Go). - Experience managing the technical pre-sales cycle, from initial scoping and architecture design to the successful delivery of integrated PoVs. - Experience with cloud-native application development. - Experience designing and building AI applications.