Applied AI Engineer

Role Overview

Key Responsibilities

• Design, develop, test, integrate, deploy, and support scalable software and AI-driven solutions.
• Translate business and technical requirements into effective technical solutions and working software.
• Build and support AI/ML and Generative AI applications, including rapid prototypes and proof-of-concepts.
• Apply AI and Agentic AI practices across the software development lifecycle.
• Use AI-powered engineering tools for code generation, code reviews, testing, debugging, and technical documentation.
• Contribute to component-level and technical architecture decisions while maintaining engineering, architecture, dependency, and coding standards.
• Participate in code reviews and continuous improvement of engineering quality and delivery practices.
• Collaborate with product management, engineering, experience, and delivery teams to deliver business-focused technical solutions.

Required Skills & Qualifications

• 3–5 years of professional software engineering experience.
• At least 1 year of hands-on experience building AI/ML applications.
• Practical experience developing Generative AI applications involving LLM integration, RAG, prompt engineering, and vector databases.
• At least 1 year of cloud-native engineering experience with a major cloud platform.
• Strong understanding of object-oriented programming, object-oriented design, data structures, algorithms, and software engineering best practices.
• Hands-on experience with at least one modern programming, application, data, or AI technology listed in the role requirements.
• Ability to work onsite at least 3 days per week in Nashville, TN or Tampa, FL.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, Machine Learning, or a related technical discipline.
• Experience with Agentic AI frameworks and AI agents.
• Exposure to Agile and DevSecOps practices.
• Experience with LangChain, LangGraph, PyTorch, TensorFlow, or cloud AI platforms such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
• Experience with GitHub, SonarQube, MLflow, or similar engineering and ML platforms.
• Experience developing production-ready AI solutions in enterprise environments.
• Travel flexibility of 0–10%.

Applicants will be asked to answer the following qualifying questions when applying for this position:

• 1Do you have at least 1 year of hands-on experience building AI/ML or Generative AI applications, including LLM integration, RAG, prompt engineering, or vector databases?
• 2Do you have at least 1 year of hands-on cloud-native engineering experience with AWS, Azure, or GCP, including exposure to services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI?
• 3Are you able to work onsite at least 3 days per week in either Nashville, TN or Tampa, FL?
• 4Are you currently authorized to work in the U.S. on a W-2 basis without employer sponsorship (U.S. Citizen, Green Card, H-4 EAD, or OPT EAD)?