Job Description
Prinicipal AI Engineer Job Poster :
Wisestep-Inc Skills:
Java, C++, PyTorch, Docker, Artificial Intelligence, Keras, Machine Learning, Python, TensorFlow, Kubernetes | Location:
Des Moines , Iowa , United States Of America Views:
16 Principal AI Engineer Must Have Technical/Functional Skills Seeking a highly accomplished Principal AI Engineer to lead the design, architecture, and delivery of enterprise scale AI and Machine Learning solutions. This role requires deep technical expertise in AI/ML, strong architectural vision, hands-on leadership, and the ability to drive AI strategy across the organization. The ideal candidate has extensive experience with advanced ML systems, GenAI/LLM solutions, and end to end AI platform development. Key Responsibilities AI Strategy & Technical Leadership • Define and drive the organization’s AI roadmap, architecture, and long-term technical vision. • Lead and mentor AI/ML engineers, data scientists, and cross-functional teams. • Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms. AI/ML Architecture & Innovation • Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation. • Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants. • Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development. End-to-End AI System Development • Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring. • Build large-scale, cloud-native AI systems using Azure/AWS/GCP. • Establish standards for model quality, reliability, interpretability, and governance. MLOps & Platform Engineering • Architect robust MLOps pipelinesâ€"CI/CD, model versioning, drift detection, automated retraining, monitoring. • Lead the development of AI platforms supporting multiple business teams and workloads. • Ensure production environments meet performance, scalability, and security requirements. Cross Functional Collaboration • Partner with executives, product teams, and business leaders to identify AI opportunities. • Translate complex business problems into scalable AI solutions. • Represent AI architecture in technical reviews and decision-making processes. • Databricks, SQL, and data processing frameworks.
