Snowflake Advanced AI Engineer

Accenture•St. Louis, MO

1d•$54,400 - $205,800

About The Position

As a Snowflake Advanced AI Engineer, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients. You will combine custom models with cloud and third-party AI services to deliver production-ready outcomes. The role spans the full solution lifecycle: assessing client needs and data, selecting and customizing models—including deep learning, generative AI, and large language models—designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring the quality, value, and reliability of deployed systems. The role is part of Accenture’s Global Agentic Center of Excellence. It involves research and development of AI and high-performance computing approaches, collaboration with business and technical teams, and integrating solutions into production. Travel may be required, ranging from 0% to 100% depending on business needs and client requirements.

Requirements

At least 2 years of hands-on experience with Snowflake Cortex AI, including Cortex Agents, Cortex Analyst, and Cortex Search.
At least 3 years of experience as a machine learning engineer or scientist deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing.
At least 3 years of experience applying theoretical computer science foundations, including computer system architecture, systems engineering, and programming.
At least 1 year of experience with distributed computing systems and architecture, which may include big data, high-performance computing, engineering simulations, scientific computing, grid and cloud computing, or distributed networks.
At least 1 year of experience building and deploying AI/ML-based software to a cloud environment.
Bachelor’s degree or equivalent (minimum 12 years) of work experience. If holding an associate’s degree, at least 6 years of work experience is required.
Strong written and verbal communication skills, including the ability to explain complex technical concepts to non-technical stakeholders.
Strong client-facing skills in a consulting environment.
Strong cross-functional collaboration skills with internal and client-side teams.
Entrepreneurial mindset, curiosity about emerging technology, and passion for driving innovation.
For U.S. employment, work authorization that does not now or in the future require visa sponsorship.

Nice To Haves

Proficiency in Python and Python-based AI/ML frameworks, with familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch.
Experience working with language models and LLM APIs and optimizing their use for specific applications.
Experience with Python, C++, Java, R, or SQL.
Master’s or Ph.D. in a related field, such as computer science or engineering.

Responsibilities

Translate real-world problems into practical, efficient, and scalable AI and machine learning solutions.
Develop and implement machine learning algorithms, models, and computational systems; design scalable data pipelines for model training and production using DevOps and MLOps.
Customize and apply deep learning and generative AI models to business use cases, considering data availability, system and infrastructure requirements, edge devices, and high-performance computing.
Research and develop AI and high-performance computing algorithms, models, and simulations and apply them to complex business problems at client sites.
Work with large-scale datasets and preprocess data to provide high-quality inputs for training and production.
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge.
Justify the value of model approaches in business problems.
Collaborate with business and technical stakeholders—including users, use case representatives, business owners, engineers, architects, and UI designers—to achieve end-to-end project goals and integrate solutions into production.
Deploy machine learning models in production at scale, including monitoring, alerting, automatic bug filing, and auditing.
Travel as required by business needs and client requirements; the stated range is 0% to 100%.