Senior Principal AI Engineer

We're looking for an experienced Senior Principal AI Engineer who will bring strategic leadership and deep subject-matter expertise in designing and implementing enterprise-scale AI/ML infrastructure, automation tools (MLOps and DevOps), and cloud-native AI solutions. Responsibilities: Leading the design, architecture, and optimization of machine learning deployment tools and automation systems that operate the business's data and ML applications Defining and implementing best practices and standards for data and machine learning pipelines across the organization Collaborating with engineers and machine learning researchers to automate code analysis, build, integration, and deployment of ML applications Providing technical guidance on infrastructure design decisions and monitoring solutions Building highly scalable, resilient cloud and on-premise systems for hosting machine learning systems using state-of-the-art technologies, including Google Cloud Platform (GCP) and Vertex AI Mentoring junior engineers and contributing to team growth and technical excellence Requirements: Extensive experience designing and implementing distributed ML systems at scale Hands-on experience with GCP services, particularly Vertex AI for model training, deployment, and monitoring Experience building and integrating Generative AI solutions, including LLMs, RAG architectures, and AI harnesses/orchestration frameworks (e.g., LangChain, LlamaIndex) Proficiency with MLOps orchestration tools such as AirFlow, KubeFlow, Dagster, or Flyte Experience with DevOps pipelines (Jenkins, GitHub Actions) Strong programming skills in Python; familiarity with Bash or JavaScript a plus Hands-on experience deploying hybrid environments across GCP, AWS, and/or Azure Familiarity with ML frameworks such as PyTorch or TensorFlow Knowledge of software engineering best practices including testing, code reviews, and source control Job Data by YubHub .