Artificial Intelligence Engineer (Remote) - Knoxville, TN

About the Role

The SOFEI Group is seeking a skilled Artificial Intelligence Engineer to innovate and deploy intelligent functionalities that enhance a SaaS product focused on the financial consulting domain. This full-time remote position works closely with product, data, and engineering teams to transform business requirements into practical AI and machine learning implementations, concentrating on solutions that boost user experience and operational efficiency.

Key Responsibilities

• Develop and deploy AI and machine learning solutions that integrate with product features, automate tasks, and enable data-driven decisions.
• Construct end-to-end machine learning pipelines including data preparation, feature engineering, model training, validation, deployment, and continuous performance evaluation.
• Collaborate with product managers, engineers, and data specialists to pinpoint impactful opportunities for automation and advanced analytics.
• Create generative AI applications such as summarization tools, recommendation systems, classification models, and agent-based interactions while optimizing for speed, quality, and cost-efficiency.
• Integrate trained models into cloud production environments using APIs, microservices, and containerization techniques.
• Evaluate external AI platforms, libraries, and third-party solutions to enhance product capabilities and engineering productivity.
• Implement responsible AI practices including monitoring model stability, mitigating bias, and maintaining data privacy and security throughout development.
• Maintain thorough technical documentation, detailed experiment logs, and reproducible development processes fostering transparency and teamwork.
• Stay current with advancements in machine learning, large language models, and SaaS technologies to suggest enhancements to tools, system architecture, and delivery strategies.

Candidate Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field, or equivalent professional experience.
• Minimum of 3 years experience in designing, deploying, and maintaining machine learning models in a production setting.
• Proficiency in backend Python development and experience with ML frameworks like PyTorch, TensorFlow, or scikit-learn.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure, along with container technologies including Docker and Kubernetes.
• Knowledge of large language models, vector databases, and modern AI tools relevant to applied machine learning.
• Understanding of API development and service-oriented software architectures.
• Strong foundation in software engineering principles encompassing algorithms, data structures, code quality, and scalable system design.
• Familiarity with model experimentation, evaluation, and continual monitoring strategies for AI systems in production.