AI Engr (Commercial & MTO)

NTT DATA Services • Dallas, TX

4d • Onsite

About The Position

AI Engineer (Commercial & MTO) responsible to build production-ready artificial intelligence and machine learning solutions to drive business growth. This role bridges software engineering, data science, and commercial strategy, typically managing the deployment of models into operational pipelines for revenue generation, market analysis, and supply chain logistics.

Requirements

• 7+ years of advanced coding skills in Python, SQL, and Java/Scala.
• Proficiency in ML frameworks like PyTorch or TensorFlow, and frameworks for building workflows like LangChain.
• 5+ years of experience deploying models using cloud platforms such as AWS, Azure, or Google Cloud (GCP), along with CI/CD pipelines.
• 5+ years of ability to explain complex AI outputs to C-suite executives and non-technical stakeholders to influence commercial decision-making.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field.
• Compliance with Client’s responsible AI principles and Acceptable Use policy
• Adherence to data residency, privacy (GDPR, HIPAA where applicable), and 21 CFR Part 11 controls where in scope
• Third-party risk assessment and SOC 2 Type II (or equivalent) certification
• Disclosure of subcontractors and offshore delivery locations
• Disclosure of model providers, training data practices, and any use of client data for model improvement (opt-out required)

Responsibilities

• Commercial AI Strategy: Collaborate with business leaders and product managers to map organizational challenges to high-impact AI/ML use cases.
• Model Deployment & API Integration: Transform trained machine learning models into robust, scalable, production-ready APIs that integrate seamlessly with enterprise systems.
• Workflow Automation (MTO): Build multi-agent AI systems, workflows, and Retrieval-Augmented Generation (RAG) architectures to optimize Make-To-Order (MTO) production pipelines and e-commerce supply chains.
• Data Pipelines & Ingestion: Develop and manage infrastructure to collect, clean, and transform unstructured data for AI model consumption.
• Performance Monitoring: Maintain and continuously optimize deployed models for accuracy, reliability, and cost-efficiency in live production environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior