Job DescriptionInside the Cloud Solutions TeamOur team is a premier, award-winning group of cloud experts specializing in the State, Local, and Education (SLED) and Higher Education sectors. Highly recognized leader in Google's exclusive SLED badge program with distinctions in AI/ML, Data & Analytics, and Work Transformation. We bring deep expertise and innovation to every engagement.
Working in close collaboration with Google Cloud sales teams, Rapid Innovation Teams, and technical SMEs, our team delivers transformative cloud solutions that help hundreds of clients modernize, innovate, and achieve meaningful outcomes.
How You'll Make an Impact As a Sr. Consultant, you serve as the hands-on technical lead for Google Cloud delivery engagements, with a primary focus on architecting, building, and deploying modern cloud infrastructure. This is a highly technical, client-facing role centered on delivery execution within complex production environments. The role requires deep expertise in Google Cloud Platform (GCP), production-grade Kubernetes, and Terraform, with the majority of time spent directly implementing and supporting cloud solutions. Pre-sales involvement is limited, particularly during the first year, with an emphasis on leading technical delivery efforts for client projects.
Key Responsibilities
- Technical Leadership & Delivery: Act as the hands-on technical lead for client delivery projects, architecting and implementing secure, scalable, and robust Google Cloud solutions.
- Infrastructure as Code & Containerization: Write, test, and deploy robust, modular, and scalable infrastructure using production-grade Terraform or OpenTofu. Design, deploy, and manage Kubernetes environments (specifically GKE) tailored to complex client workloads, including GPU-accelerated clusters for modern machine learning applications.
- AI Infrastructure Architecture: Lead the design and deployment of foundational cloud infrastructure required for enterprise AI workloads, such as securing Vertex AI environments, configuring MLOps pipelines, and establishing secure networking for LLM deployments.
- Client Communication: Lead technical discussions with a variety of client stakeholders ranging from central IT and research teams to non-technical project sponsors. Translate complex technical concepts into clear, actionable business insights.
- Project Execution: Work closely with internal and client Project Managers to ensure milestones are met, navigating and resolving technical ambiguity along the way.
- Mentorship & Collaboration: Serve as a technical mentor to Consultants and Associate Consultants on the team, fostering a culture of continuous learning and high performance.
QualificationsYour Core Skills & Certifications - Deep Google Cloud Expertise: Extensive, hands-on experience designing and deploying infrastructure natively on GCP. (Note: We are looking for native GCP proficiency; while AWS/Azure experience is a minor plus, it does not replace the need for strong Google Cloud skills).
- Kubernetes in Production: Deep understanding of Kubernetes architecture and hands-on experience running, deploying, and managing K8s clusters in production environments (GKE preferred).
- Advanced IaC: Extensive, hands-on experience writing and managing production-ready Terraform (or OpenTofu), including state management, modules, and CI/CD integration.
- Adaptable & Self-Motivated: Ability to thrive in ambiguous project environments, take initiative, and drive solutions forward independently.
- Excellent Communicator: Highly professional communication skills with the emotional intelligence to navigate complex client relationships and varying levels of technical literacy.
- Continuous Learner: A genuine passion for staying ahead of the curve on emerging cloud technologies, modern DevOps/Platform Engineering practices, and secure AI/ML integrations within the Google ecosystem.
- Team Player: You collaborate effectively with others, welcome feedback and code reviews from senior team members, and contribute positively to a team-oriented environment.
Preferred Qualifications
- MLOps & AI Foundations: Experience or strong interest in architecting the infrastructure for generative AI workloads, including an understanding of LLM serving requirements, vector database provisioning, and deploying agentic frameworks.
- Certifications: Active Google Cloud Professional Certifications (e.g., Cloud Architect, Cloud DevOps Engineer, Machine Learning Engineer) are highly preferred. CNCF (CKA/CKAD) or HashiCorp certifications are a strong plus.
Additional Information 
