AI Principal Engineer

The AI Principal Engineer (IC Director) is responsible for leading the design, development, and delivery of complex, production-grade AI solutions that drive meaningful business outcomes. This role serves as a senior technical leader across multiple initiatives, owning significant platform components and domains while influencing architecture, engineering standards, and solution quality.

Operating with a high degree of independence, the AI Principal Engineer partners closely with product, engineering, data, and governance stakeholders to deliver scalable, reliable, and secure AI solutions in a highly regulated environment. This role plays a critical part in ensuring AI capabilities are aligned to enterprise standards, responsible AI principles, and long-term business objectives.

This role is fully remote, with no regular in-office requirement.

- Lead the design, development, and deployment of complex AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) pipelines, and model-driven services. - Own technical direction for major AI platform components, products, or functional domains. - Establish and drive engineering best practices for model evaluation, validation, testing, monitoring, and operationalization. - Partner with product, business, and data stakeholders to translate business requirements into scalable AI solutions. - Contribute to architectural decisions related to model selection, system integrations, API design, and platform scalability. - Ensure AI solutions comply with enterprise standards for security, privacy, governance, and responsible AI. - Mentor and guide engineering team members while promoting technical excellence and engineering quality. - Identify technical risks, dependencies, and implementation challenges, and develop appropriate mitigation strategies. - Drive delivery outcomes across multiple initiatives while maintaining high standards for reliability, performance, and maintainability. - Influence engineering practices and contribute to continuous improvement across AI development and deployment processes.

- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field required. - Significant experience designing, developing, and delivering production AI/ML systems. - Experience deploying, operationalizing, and maintaining AI/ML models in production environments. - Strong proficiency in programming languages such as Python, TypeScript, or Rust. - Experience with AI/ML frameworks, large language model (LLM) technologies, and modern data pipelines. - Deep understanding of model lifecycle management, MLOps practices, and production reliability principles. - Demonstrated success leading complex technical initiatives with significant business impact. - Strong analytical, problem-solving, and systems-thinking capabilities. - Proven ability to collaborate effectively across technical and non-technical disciplines.

- Advanced degree in Computer Science, Engineering, Mathematics, or a related field preferred. - Experience building and supporting enterprise-scale generative AI solutions. - Experience with retrieval-augmented generation (RAG), vector databases, and AI orchestration frameworks. - Familiarity with cloud-native AI platforms and modern distributed system architectures. - Experience operating within regulated industries and governance-focused environments. - Knowledge of responsible AI frameworks, model risk management, and AI compliance practices. - Experience mentoring engineers and influencing technical strategy across multiple teams.