AI Application Developer

Job Summary: We are seeking an AI Application Developer to join our U.S.-based AI Application Solutions team. You will design and develop AI-driven software solutions that translate machine-learning models, predictive analytics, anomaly detection, and large-language-model reasoning into scalable, reliable backend services and applications.

This is a hybrid role based in our office in Morrisville, NC

Roles and Responsibilities:

Design and Implementation

• Design and develop AI-driven software solutions that translate machine-learning models, predictive analytics, anomaly detection, and large-language-model reasoning into scalable, reliable backend services and applications.
• Build, test, and maintain enterprise-grade applications using Python, leveraging frameworks such as FastAPI, Flask, or Django, with a focus on clean architecture, modular design, and maintainability.
• Develop and integrate machine-learning pipelines for training, evaluation, deployment, and monitoring of models using libraries such as scikit-learn, TensorFlow, PyTorch, or similar.
• Implement LLM-powered capabilities including semantic search, intelligent assistants, automated summarization, and recommendation systems using modern AI frameworks and APIs.
• Design and optimize data processing workflows for structured and unstructured data, ensuring performance, scalability, and reliability in high-volume production environments.
• Collaborate closely with data scientists, AI/ML engineers, and frontend teams to align model outputs with application logic, APIs, and user-facing requirements.
• Build and maintain APIs and services that expose AI and ML functionality securely and efficiently to internal and external consumers.
• Implement logging, monitoring, and analytics to track model performance, system health, feature adoption, and workflow bottlenecks.

• Ensure best practices in software engineering, including unit testing, integration testing, CI/CD pipelines, version control, and code reviews.
• Optimize system performance, reliability, and scalability across cloud or hybrid environments.
• Translate business and operational requirements into robust technical solutions that improve automation, decision-making, and overall system intelligence.
• Own the end-to-end functionality of AI-enabled software components, from development through deployment and ongoing optimization.