Principal AI/ML Engineer 15+ Years Experience JOB SUMMARY We are seeking a Principal AI/ML Engineer to set the technical vision and standards for Artificial Intelligence across the enterprise. The ideal candidate is a recognized expert in architecting and scaling Machine Learning and Generative AI platforms, combining deep technical mastery with strategic influence. You will define architecture and direction for AI initiatives spanning LLMs, Agentic AI, Retrieval-Augmented Generation (RAG), MLOps/LLMOps platforms, Intelligent Automation, and enterprise-scale AI solutions. As the senior-most individual contributor, you will drive the AI technical strategy, establish organization-wide standards and governance, lead the most complex programs, and act as a trusted advisor to senior engineering and business leadership. KEY RESPONSIBILITIES Define the technical vision, architecture, standards, and multi-year roadmap for enterprise AI and Generative AI platforms. Architect the most complex, large-scale ML and LLM systems, setting the direction others build on. Establish organization-wide best practices for RAG, Agentic AI, model selection, evaluation, and safety. Own the strategy and architecture for the enterprise MLOps/LLMOps platform, enabling scalable, reliable AI delivery. Set and govern responsible-AI, security, guardrail, and regulatory-compliance standards across all AI work. Drive build-vs-buy and platform strategy; lead evaluation and selection of models, vendors, and core tooling. Lead the most complex, high-risk cross-functional programs from vision through production. Serve as a technical authority and mentor across the AI organization, growing senior and staff engineers. Partner with senior business and technology leadership to shape AI strategy, prioritize investments, and quantify enterprise impact. Represent the AI function in architecture-governance forums and establish reusable platforms and accelerators across the enterprise. Anticipate the evolving AI landscape and translate emerging research into pragmatic, high-value enterprise capabilities. Champion a culture of technical excellence, innovation, and continuous improvement. REQUIRED QUALIFICATIONS Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (advanced degree strongly preferred). 15+ years of professional experience in AI, Machine Learning, or software engineering, with extensive time architecting and scaling production AI systems. Recognized expert-level Python and software-architecture capabilities. Proven track record defining and delivering enterprise-scale Generative AI and LLM platforms. Deep mastery of agentic AI, advanced RAG, and large-scale distributed AI systems. Authority-level expertise in MLOps/LLMOps, platform engineering, and lifecycle automation. Extensive multi-cloud experience (Azure, AWS, or Google Cloud) and large-scale distributed systems. Demonstrated strategic technical leadership: setting direction, governance, and standards across teams. Deep expertise in responsible AI, security, governance, and cost optimization at scale. Exceptional communication and influencing skills with senior technical and executive stakeholders. PREFERRED SKILLS Mastery of the modern AI stack: PyTorch, TensorFlow, Hugging Face, and distributed training/inference at scale. Deep production experience across multiple LLM providers (OpenAI, Anthropic Claude, Azure OpenAI, Gemini) and open-weight models. Expertise in fine-tuning, LoRA/PEFT, distillation, and high-performance model serving (vLLM, TGI, Triton). Authority-level experience with vector databases and large-scale retrieval architectures. Expertise across orchestration and platform tooling such as Kubernetes, Airflow, and Ray. Track record of building AI Centers of Excellence, enterprise platforms, and reusable accelerators. Thought leadership: patents, publications, keynote talks, or significant open-source contributions. Experience shaping AI strategy and governance at an organizational or enterprise level. WHAT THIS ROLE OFFERS Ownership of the enterprise AI and Generative AI technical strategy and platforms. The mandate to architect and scale next-generation Agentic AI and LLM systems. Influence over organization-wide standards, responsible-AI practices, and governance. A leadership seat in the most strategic business-transformation programs. The opportunity to shape the long-term AI vision and grow the next generation of AI leaders.