AWS Solutions Architect- AI/ML

Position Title: AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with travel required.

About Cloudelligent Cloudelligent is an AWS Premier Consulting Partner helping organizations modernize, migrate, and innovate in the cloud.

We work at the intersection of cloud, data, and AI to solve real business problems and not just implement technology.

With an international footprint, Cloudelligent is customer-obsessed and focuses on Generative AI and Agentic AI to deliver practical, scalable solutions.

Job Objective As an AWS Solutions Architect- AI/ML at Cloudelligent, you will be responsible for designing and implementing scalable, innovative cloud solutions for our clients.

You will focus on cloud modernization, data engineering, and AI/ML integration to drive business transformation.

You will collaborate with clients, service delivery managers, and cross-functional teams to understand business goals, assess existing infrastructure, and develop cloud architectures using AWS technologies.

• Architect cloud-native solutions and lead app modernization initiatives to migrate legacy applications to AWS, improving scalability, performance, and cost efficiency.
• Design and implement cloud solutions that integrate data engineering, Generative AI, and machine learning (ML) technologies to enhance business operations, customer experiences, and automation.
• Lead technical presales discussions, collaborating with sales teams to understand client needs and design cloud solutions that leverage AI, data, and modernization strategies.
• Act as a trusted advisor, guiding clients through the design and implementation of custom cloud architecture that meet their business goals, with a focus on scalability, security, and cost optimization.
• Lead deep-dive architecture sessions with clients, proposing Well-Architected solutions that include data pipelines, cloud-native frameworks, and modern technologies for app modernization, AI/ML, and data-driven applications.
• Define and implement cloud governance frameworks to ensure compliance with AWS security policies, industry standards, and best practices for data security, AI privacy, and regulatory compliance.
• Collaborate with internal teams to ensure smooth knowledge transfer from pre-sales to delivery teams, ensuring project goals, timelines, and expectations are clearly set.