Snowflake AI Solution Lead: Gen AI & ML Architect

Accenture; Oklahoma City (OK); On-site; USD 90,000 - 180,000; Full time

Job summary

Accenture seeks a Snowflake Advanced AI Solution Lead to design, build, and operationalize AI/ML solutions for enterprise clients, combining custom models with cloud services to deliver production-ready outcomes.

You will manage the full solution lifecycle—from needs assessment and data preparation to model deployment, scalable data pipelines, and MLOps—working with cross-functional teams to ensure value and reliability.

Qualifications

• Minimum of 2 years hands-on Snowflake Cortex AI experience.
• Minimum of 5 years as a machine learning engineer or scientist deploying models at scale.
• Minimum of 5 years applying theoretical foundations of computer science and system engineering.
• Minimum of 3 years in distributed computing systems and cloud computing.
• Minimum of 2 years building and deploying AI/ML software to a cloud environment.
• Bachelor's degree or equivalent (minimum 12 years) work experience.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement ML models, data pipelines, and DevOps/MLOps for training and production.
• Customize Deep Learning and Gen AI models based on business needs and data availability.
• Engage in R&D of new AI algorithms and simulations for client applications.
• Work with large-scale datasets and data preprocessing for high-quality training inputs.
• Implement and maintain efficient data storage and retrieval for models and knowledge.
• Justify the value of model approaches in business problems.
• Collaborate with business and technical teams to deliver end-to-end production deployments.

Job description

Accenture seeks a Snowflake Advanced AI Solution Lead to design, build, and operationalize AI/ML solutions for enterprise clients, combining custom models with cloud services to deliver production-ready outcomes.

You will manage the full solution lifecycle—from needs assessment and data preparation to model deployment, scalable data pipelines, and MLOps—working with cross-functional teams to ensure value and reliability.