GenAI Data Automation Engineer (Public Trust Required) (Remote Position) - Atlanta, GA

We are looking for an Artificial Intelligence (AI) Engineer to create and expand advanced AI solutions that support real-world business applications in Atlanta, Georgia. This position is ideal for a hands-on engineer who can turn emerging AI concepts into reliable production systems, from intelligent workflows to scalable backend services. The role blends applied machine learning, large language model integration, and software engineering to deliver secure, high-performing tools in an enterprise setting.

Responsibilities

• Design and develop AI-driven applications that combine machine learning models, large language models, and backend services for production use.
• Create prompt frameworks, retrieval approaches, and context-handling strategies that improve the relevance and reliability of AI-generated outputs.
• Build intelligent agents and automated workflows that support business processes and interact effectively with enterprise data sources.
• Integrate tools such as TensorFlow, vector databases, and orchestration frameworks to support scalable AI and computer vision solutions.
• Measure model and system effectiveness by monitoring accuracy, latency, stability, and overall operational performance.
• Improve deployed solutions through performance tuning, cost optimization, and troubleshooting across cloud-based environments.
• Collaborate with product, engineering, and user experience teams to deliver AI features that align with business goals and user needs.
• Contribute reusable components, shared services, and engineering best practices that strengthen the broader AI platform.
• Support detection and computer vision use cases where image-based analysis and machine learning capabilities are required.
• Extensive experience developing software solutions with Python; Node.js experience is also valuable.
• Hands-on knowledge of large language model APIs and practical implementation of AI-powered application features.
• Familiarity with frameworks and tooling used for LLM orchestration, such as LangChain, LlamaIndex, or similar technologies.
• Experience working with vector databases, retrieval systems, and context-aware AI architectures.
• Understanding of the end-to-end AI and machine learning lifecycle, including development, deployment, monitoring, and maintenance.
• Background building solutions in cloud environments such as AWS, Azure, or comparable platforms.
• Solid backend engineering skills, including API development, system integration, and production troubleshooting.
• Exposure to computer vision, detection models, TensorFlow, ChatGPT, GPT, or related AI technologies is strongly preferred.