Sr. Consultant, Cloud Solutions
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Job description
Our 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., 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., * 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.
Requirements
- 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.