Job description

Principal Engineer - Enterprise Applications & AI- Director level Direct hire role Hybrid- 3 days per week in office Location- Dallas TX/ Chicago IL/ NYC (Total Comp range is based on the experience and skills level) We are seeking an experienced, strategic, and hands-on Principal AI Engineer. In this leadership role, you will drive the vision, strategy, and implementation of enterprise-grade AI and machine learning solutions across the organization. As the lead AI expert, you'll collaborate closely with application architects, domain experts, data scientists, and product leaders to design, develop, and scale AI systems that enhance business value and innovation. Responsibilities: • Strategic Leadership: Define and implement a comprehensive AI vision and strategy to accelerate enterprise AI adoption, enhance competitive advantage, and foster innovation. • Enterprise AI Solutions: Architect and deliver scalable, production-grade AI pipelines covering the full lifecycle from model development and deployment to monitoring and optimization. • Advanced AI Development: Lead the fine-tuning, customization, and deployment of foundation models, including LLMs, vision, multi-modal models, and intelligent agents. • Platform and Infrastructure Development: Establish and evolve robust Data and AI platforms to enable rapid iteration, experimentation, and adoption across enterprise applications. • AI Technology Evaluation: Evaluate and select optimal SaaS products and platforms to accelerate AI-driven development, operational efficiency, and scalable deployment. Required Skills and Experience: • Extensive experience leading enterprise-level AI initiatives and successful AI-driven transformations. • Deep expertise in advanced Machine Learning and AI methodologies, including optimization, forecasting, and simulation. • Proficiency in managing and optimizing full lifecycle MLOps, including model development, deployment, monitoring, and lifecycle management. • Strong technical knowledge of foundation models, including LangChain/LLMOps, and experience with customizing large-scale language and multimodal models. • Hands-on experience with cloud-based AI infrastructure (Azure, AWS, GCP). • Expert-level proficiency in Python, PyTorch/TensorFlow, Docker/Kubernetes. • Demonstrated ability to optimize AI and ML platforms, data pipelines, and workflows to maximize efficiency and scalability.

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