Principal AI-ML Engineer

Principal AI/ML Engineer

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

• Bachelors or Masters 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.