Snowflake GenAI Engineer for Enterprise ML/LLMOps

Accenture; United States; On-site; USD 105,000 - 190,000; Full time

Job summary

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

The role covers the full lifecycle from data assessment to model customization, training, deployment, and monitoring across Gen AI, DL, and LLMs, with a strong emphasis on scalable data pipelines and MLOps practices.

Qualifications

• Minimum of 2 years of hands-on experience with Snowflake Cortex AI and Cortex Agents/Analyst/Search.
• Minimum of 3 years of experience as a machine learning engineer or scientist deploying models in production at scale.
• Minimum of 3 years of experience in computer science fundamentals including system architecture and programming.
• Minimum of 1 year of distributed computing or big data experience.
• Minimum of 1 year of building and deploying AI/ML software to a cloud environment.
• Bachelor's degree or equivalent work experience (12 years).

Responsibilities

• Formulate real-world problems into scalable AI/ML solu­tions.
• Develop and implement ML models and data pipelines with DevOps & MLOps.
• Customize Deep Learning and Gen AI models based on business needs.
• Research new AI algorithms and high-performance compute techniques.
• Work with large datasets and ensure high quality training data.
• Store and retrieve model knowledge efficiently.
• Justify model approaches for business impact.
• Collaborate with cross-functional teams to deliver end-to-end projects.

Skills

Snowflake Cortex AI

Machine learning engineering

CS fundamentals

Distributed computing

Cloud deployment

Communication

Client-facing

Cross-functional collaboration

Entrepreneurial mindset

Python

LLM APIs

C++

Java

R

SQL

Education

Bachelor's degree or equivalent

Job description

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

The role covers the full lifecycle from data assessment to model customization, training, deployment, and monitoring across Gen AI, DL, and LLMs, with a strong emphasis on scalable data pipelines and MLOps practices.