Applied AI Engineer

experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering. • Experience building, delivering, or supporting AI-enabled solutions using Large Language Models (LLMs), Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), vector databases, AI orchestration frameworks, or related AI technologies in enterprise environments.

Primary Skill Required for the Role: AI & Data Testing
Level Required for Primary Skill: Advanced (6-9 years experience)

Additional Details for Role:
- Will operate as Applied AI Engineer
- Preferred Location - Nashville or Tampa
- 10% travel to either locations is required.
- Advanced to Expert level experience required.


• Experience building, delivering, or supporting AI-enabled solutions using Large Language Models (LLMs), Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), vector databases, AI orchestration frameworks, or related AI technologies in enterprise environments.
• Understanding of Responsible AI principles, including AI governance, security, privacy, transparency, human oversight, and model evaluation best practices.
• Demonstrated ability to effectively leverage AI tools and assistants to improve individual productivity, accelerate delivery, enhance decision-making, automate routine tasks, and improve quality across day-to-day work activities.
• Strong AI literacy, including the ability to evaluate AI-generated outputs, apply critical thinking and human judgment, and identify appropriate use cases for AI-driven solutions.
• Preferred: Hands-on experience with Python and/or .NET technologies for developing, integrating, and operationalizing AI-enabled applications and services.
• Continuous learner with a passion for staying current on emerging AI technologies, practices, and industry trends.
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Preferred Skills (Recommended for All Engineering-Focused Applied AI Roles)
• Experience with Python, .NET, cloud-native application development, APIs, microservices, and modern software engineering practices.
• Experience with Azure OpenAI, Azure AI Foundry, Microsoft Copilot technologies, AI orchestration frameworks, vector databases, and enterprise AI platforms.
• Experience developing, integrating, deploying, or operating AI-enabled applications in Azure cloud environments.
• Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g. LangFuse, LangSmith, or equivalent multi-agent orchestration tools) etc. to deliver high-quality products rapidly.
• experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering.
• Prior experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks.
• Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.