Solutions Architect (Artificial Intelligence / Machine Learning)

Are you passionate about shaping the future of artificial intelligence and machine learning? Join us to architect innovative solutions that accelerate business outcomes and transform how organizations leverage data. As a Solutions Architect, you will collaborate with talented teams to build resilient, cloud-based platforms that power advanced analytics. Your expertise will help drive operational excellence, security, and compliance across our technology landscape. Be part of a dynamic environment where your ideas and skills make a real impact.

As a Solutions Architect (AI / ML) in the Enterprise Data Solutions and Data Analytics team, you design, implement, and scale machine learning and generative AI solutions in the cloud. You act as a trusted advisor, guiding us in building secure, high-performance, and cost-efficient AI platforms that accelerate business outcomes. You collaborate with development, data science, and analytics teams to define cloud strategies, ensure seamless integrations, and optimize performance across cloud and hybrid environments. You select the right tools and technologies to build resilient platforms that meet our business needs while maintaining security, compliance, and operational excellence. Together, we shape the technology strategy of our organization.

Job Responsibilities

• Designs and implements end-to-end architectures for AI / ML workloads, including data ingestion, model training, deployment, and monitoring
• Oversees the deployment of AI models and applications from development through production, ensuring reliability, security, and cost-efficiency.
• Advises on scalable infrastructure for generative AI, foundation models, and data-driven applications.
• Monitors, maintains, and optimizes AI infrastructure to support high availability and performance.
• Automates infrastructure provisioning and management using Terraform and other infrastructure-as-code tools.
• Supports enterprise migrations of AI / ML pipelines from on-premises or legacy systems to the cloud.
• Collaborates with data science, product, and engineering teams to accelerate AI adoption across the organization.
• Creates and maintains architecture documentation, standards, and best practices for data pipelines and ETL frameworks
• Champions best practices for security, compliance, and ethical AI using AWS technologies. Delivers workshops, proof-of-concepts, and executive briefings to showcase AI / ML best practices.
• Drives conversations on security, compliance, and responsible AI in large-scale environments. Mentors engineering and data teams, helping them operationalize and optimize AI solutions.

Required Qualifications, Capabilities, and Skills

Preferred Qualifications, Capabilities, and Skills

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