Principal AI Engineer

Manhattan Associates • Atlanta, GA

2d

About The Position

We create possibilities that move life and commerce forward Welcome to Manhattan. Every day, our supply chain commerce technology connects two billion people to 20 billion consumer choices. In the warehouse, on the road and in the store, we make what was once impossible, possible. If you want to tackle complex problems and redefine markets, you’ve come to the right place. Principal AI Engineer is a senior technical leader responsible for designing, developing, and guiding the implementation of advanced artificial intelligence systems that support business goals. They combine deep expertise in machine learning, data science, and software engineering with strategic leadership to drive AI initiatives across an organization. They will drive the adoption of AI solutions by evangelizing their value, educating stakeholders, and guiding teams to integrate scalable and responsible AI capabilities into products and business processes.

Requirements

• 7+ years of industry experience in software engineering, machine learning, or AI roles, with a focus on developing, deploying, and scaling ML/AI solutions.
• 3+ years of proven experience in designing large-scale AI systems and defining technical roadmaps.
• Strong experience developing AI-driven workflows using eknowledge platforms, and AI agent frameworks such as Microsoft Copilot, Glean, and Google Agentspace
• Deep knowledge of: Machine Learning (classification, regression, clustering, recommendation systems) Deep Learning (CNNs, RNNs, Transformers, GANs) Natural Language Processing (BERT, GPT, LLM fine-tuning) Computer Vision (YOLO, ResNet, object tracking, OCR)
• Expertise in: Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn, Hugging Face) Data engineering and pipeline development (Airflow, Spark, ETL systems) MLOps, model lifecycle management, and production-grade deployment Cloud platforms (AWS/GCP/Azure), containerization (Docker), orchestration (Kubernetes)
• Track record of scaling ML models from experimentation to production across teams or business units.
• Design and implement integrations using Model Context Protocol to connect AI models with external tools, APIs, and data sources.
• Demonstrated ability to set research and development direction based on business needs.
• Possesses and applies moderate to complex knowledge of particular product or platform to the completion of assignments
• 3+ years experience interfacing and partnering with vendors
• 3+ years experience assisting in strategy/roadmap and planning
• Strong communication skills and ability to communicate at all levels of the organization (technical and business)
• 2+ years experience leading/mentoring more junior staff members
• Highly self-motivated, directed, ability to work independently and be results-driven
• 5+ years experience with SharePoint for document management and sharing
• 5+ years experience with IT ticketing software (Quality Center, ServiceNow, JIRA)
• 3+ years experience in agile/waterfall software delivery methodologies
• 3+ years experience using Jira, Bitbucket and Confluence agile toolsets or similar
• 5+ years experience working with small, geographically distributed teams
• 5+ years experience working both independently and in a team oriented, collaborative environment
• Ability to be flexible while delivering assignments with understanding that deliverables may change based on business needs.

Responsibilities

• AI Architecture & Strategy: Design scalable AI/ML architectures and define long-term AI technology strategy aligned with business objectives.
• Model Development: Lead development of machine learning, deep learning, and generative AI models for production environments.
• Technical Leadership: Mentor AI engineers, data scientists, and ML engineers; set engineering standards and best practices.
• Research & Innovation: Evaluate emerging AI technologies and integrate cutting-edge methods into products and platforms.
• Production Deployment: Oversee model deployment, monitoring, optimization, and lifecycle management in cloud or on-prem environments.
• Cross-Functional Collaboration: Work closely with product managers, data engineers, and business stakeholders to translate requirements into AI solutions
• Responsible AI & Governance: Ensure ethical AI practices, model explainability, fairness, privacy, and regulatory compliance.
• Performance Optimization: Improve model accuracy, efficiency, scalability, and reliability for enterprise-scale systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 501-1,000 employees