Senior Solutions Architect - Cloud & AI Optimization

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Solutions Architect - Cloud & AI Optimization based in United States. This is a senior, hands-on architecture and consulting role focused on helping enterprise customers optimize complex cloud environments.

You’ll lead FinOps and cloud cost-optimization initiatives that connect technical architecture decisions to measurable financial outcomes.

Working directly with senior stakeholders, you’ll uncover inefficiencies, shape optimization strategies, and guide implementation across engineering teams.

The role combines AWS architecture, large-scale data analysis, automation, and financial visibility with strong client advisory skills.

You’ll also influence governance, reporting, developer workflows, and engineering practices that sustain cloud efficiency over time.

AI-enabled engineering and analytics are encouraged as practical tools for increasing productivity and reducing operational effort.

This is an opportunity to deliver high-impact modernization and optimization programs where your recommendations can generate significant business value.

Accountabilities

• Lead cloud cost-optimization and FinOps initiatives across large, complex enterprise environments, identifying waste, inefficiencies, and architectural opportunities.
• Analyze cloud usage, cost, and spending patterns to uncover optimization opportunities and prioritize actions based on business impact.
• Develop and implement sustainable cloud governance frameworks, including cost allocation, showback, chargeback, rightsizing, Savings Plans, and Reserved Instance strategies.
• Partner with engineering teams to translate optimization recommendations into practical technical changes and measurable improvements.
• Design and optimize reporting, analytics, and decision-support solutions that provide customers with greater visibility into cloud financial performance.
• Work with large-scale cloud cost and usage datasets and build insights that support data-driven optimization decisions.
• Lead customer discovery sessions, optimization reviews, technical discussions, and presentations for both technical and business stakeholders.
• Build trusted-advisor relationships by clearly explaining complex technical concepts, framing problems effectively, and connecting recommendations to business outcomes.
• Guide engineering and data teams, establish cloud-efficiency best practices, and mentor team members.
• Drive architecture decisions that improve technical performance, operational efficiency, and financial outcomes.
• Explore AI-enabled engineering and analytics workflows that increase productivity, automate repetitive work, and improve optimization processes.

Requirements

• Demonstrated professional experience in FinOps and cloud cost optimization; meaningful FinOps experience is essential.
• Strong hands-on AWS experience, including familiarity with AWS-native analytics services such as Athena.
• Strong SQL and Python skills, with experience applying them to large-scale data analysis, automation, reporting pipelines, and data-transformation workflows.
• Experience with cloud cost and usage reporting, data modeling, cost governance, and financial visibility initiatives.
• Practical knowledge of cloud optimization techniques, including rightsizing, Savings Plans, Reserved Instances, cost allocation, showback/chargeback, and cloud economics.
• Proven track record of driving measurable cloud cost reductions and connecting technical improvements to financial outcomes.
• Customer-facing consulting experience, with the ability to lead discovery, advise senior stakeholders, and communicate technical recommendations clearly.
• Strong executive communication, stakeholder management, problem-framing, and data-driven decision-making skills.
• Hands-on experience with automation, reporting, and analytics systems.
• Familiarity with medallion architecture concepts and large-scale data environments.
• Experience with Kubernetes, cloud-native platforms, or containerized workloads is preferred.
• Experience using AI tools in engineering or analytics workflows, including familiarity with LLMs and AI-assisted development, is a plus.
• Strong analytical, detail-oriented, curious, and outcome-focused mindset with the ability to solve complex problems independently.

Benefits

• Fully remote…