Are You Ready?
CAI is a professional services company established in 1996 that has grown year over year to nearly 800 people worldwide. For Mission Critical and regulated industries that need to deliver critical solutions in high-stakes environments, we provide accelerated operational readiness and unparalleled performance at the highest standard through our rigorous approach, field tested processes, and elite expertise developed over 30 years.
Our approach is simple because our Purpose informs everything we do:
• We exist to be the trusted solution for our clients as they strive to build a better working world and improve the human experience.
At CAI, we are committed to living our Foundational Principles, both professionally and personally:
• We act with integrity
• We serve each other
• We serve society
• We work for our future
At CAI, we believe in a relentless dedication to excellence, pushing boundaries and surpassing expectations. From the beginning, we’ve challenged ourselves to do what others wouldn’t. Not just setting industry standards but redefining them entirely. We are bold in our thinking and creative in our approach. We operate at the intersection of wisdom and technology and thrive when they come together with humanity. For us, operational readiness isn’t simply a goal. It’s a way of life. Because tomorrow demands to be at the forefront of today. We do this through tireless effort, precision, efficiency and an unwavering belief that there is always room for advancement. We’re not interested in how it used to be done. We’re obsessed with how it will be done.
Position Overview
We are seeking an experienced Solutions Engineer with extensive AI/ML experience to join our Technology team. This is a fully remote role within the United States, reporting to the Director of Information Technology, and will be instrumental in designing and deploying scalable machine learning and business intelligence solutions that directly serve business needs. The ideal candidate has strong experience in model development and deployment, combined with a solid foundation in modern data platforms such as Snowflake.
Reports to: Director, Information Technology
Key Responsibilities
Model Development & Deployment
Design, train, and optimize machine learning models for tasks such as prediction, classification, ranking, or generative AI.
Build production-ready ML pipelines using Python, SQL, and modern orchestration tools.
Deploy models in scalable, secure, and monitored environments using MLOps best practices.
Data Engineering Integration
Work with data teams to access and manipulate large datasets, primarily within Snowflake.
Build end-to-end solutions that connect data ingestion, transformation, modeling, and output delivery.
Collaborate on building data and ML pipelines that are integrated with orchestration tools and ETL platforms.
Write and maintain SQL models using dbt and Snowflake.
Collaboration & Architecture
Collaborate with Solution Architects and cross-functional stakeholders to design ML components that fit into larger enterprise systems.
Provide input on system design, infrastructure scalability, and model performance in production.
Understand CAI Internal System infrastructure to effectively build models for internal business intelligence reporting.
Mentorship & Innovation
Mentor junior engineers and data scientists, sharing best practices and offering technical guidance.
Research and propose new methods, tools, and models to improve existing ML workflows.
Qualifications and Experience
Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
5+ years of hands-on experience in machine learning engineering roles.
Strong experience with Snowflake, including working with large datasets, writing performant SQL, and integrating ML workflows with Snowflake.
Proficiency in Python and machine learning libraries such as PyTorch, TensorFlow, Scikit-learn.
Experience deploying ML models using MLOps tooling (e.g., MLflow, Airflow, Docker, Kubernetes).
Familiarity with cloud platforms (AWS, GCP, or Azure).
Critical Competencies
Experience with Matillion or Fivetran for ETL/ELT and data integration workflows and data ingestion.
Experience with dbt, GitHub and integrated development environment (IDE) software.
Experience working with large language models (LLMs), RAG architectures, or vector databases.
Exposure to real-time or streaming model inference.
Experience with CI/CD practices and infrastructure-as-code in ML environments.
Comfortable working in regulated data environments or with PII/PHI.
What We Offer
Flexible working hours and a high degree of autonomy.
A collaborative environment that values innovation, continuous learning, and knowledge sharing.
Competitive compensation, including performance-based incentives and benefits.
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