Applied AI Engineer
ICW Group•San Diego, CA
•Hybrid
About The Position
The Applied AI Engineer is responsible for developing, deploying, and maintaining applied generative AI solutions that support the organization’s insurance products, internal workflows, and customer experiences. This role focuses on building reliable AI models and pipelines, collaborating closely with cloud engineering, AI, and ML Ops teams, and implementing best practices for model performance, security, and cost efficiency. The engineer will contribute to AI initiatives while developing expertise in generative AI, cloud deployment, and feature engineering using Snowflake.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related technical discipline.
- 3+ years of experience in AI/ML engineering, with at least 1–2 years focused on generative AI or large language models.
- Hands-on experience deploying AI/ML models in cloud environments, preferably AWS.
- Familiarity with Snowflake for AI/ML feature engineering and data integration.
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
- Knowledge of MLOps practices, including CI/CD pipelines, testing, and monitoring.
- Familiarity with containerization (Docker, Kubernetes) and deployment in cloud environments.
- Solid understanding of data pipelines, Snowflake architecture, and ETL/ELT best practices.
- Awareness of security, governance, and compliance considerations for AI/ML systems.
- Ability to troubleshoot model performance and optimize workloads for efficiency and cost.
- Strong problem-solving and collaboration skills, with effective communication to both technical and non-technical stakeholders.
Nice To Haves
- Experience in regulated industries or highly data-sensitive environments is a plus.
- AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect is preferred but not required.
- Optional AI/ML certifications (e.g., TensorFlow Developer, Hugging Face Course, or Generative AI specialization) are a plus.
- Awareness of compliance and governance standards (SOC 2, ISO 27001) is beneficial.
- Understanding of generative AI architectures, including transformers and retrieval-augmented generation.
Responsibilities
- Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and testing in production environments.
- Collaborate with cloud engineering, AI, and ML Ops teams to operationalize AI workloads on AWS using services such as SageMaker, Lambda, ECS/EKS, and S3.
- Build and maintain AI/ML pipelines leveraging Snowflake for feature engineering and data preprocessing.
- Follow organizational security and compliance standards when developing and deploying AI solutions.
- Monitor model performance, troubleshoot issues, and implement optimizations for reliability and cost efficiency.
- Participate in research and evaluation of generative AI technologies to inform project decisions.
- Document AI models, pipelines, and processes for team knowledge sharing and compliance.
- Support senior engineers in AI architecture reviews, code reviews, and operationalization planning.
Benefits
- Generous medical, dental, and vision plans
- 401K retirement plans and company match
- Bonus potential for all positions
- Paid Time Off
- Paid holidays throughout the calendar year
- Support for continued learning
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
