Engineering Leader, CloudBees

• We’re looking for someone with startup experience, a passion for AI & ML tooling, and deep understanding of operationalizing AI/ML workflows
• 7+ years of engineering experience, including platform engineering, system development, or related roles with at least 3 years in leadership roles
• 3 years of experience with large-scale systems, with a focus on reliability, scalability, and maintainability; and 1 year of experience with AI/ML systems
• Strong hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Airflow, Metaflow)
• Proven track record building ML pipelines in production environments
• Experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)
• Deep knowledge of CI/CD practices as they relate to ML lifecycle
• Prior experience in a startup or fast-paced SaaS environment
• Strong collaboration and communication skills
• Experience deploying and managing services such as Amazon bedrock or Vertex AI - LLm

Desirable

• CloudBees is seeking a visionary and hands-on Engineering Leader to drive our Agentic & AI Operations (AIOps) strategy
• Lead the development of the Cloudbees AI platform designed to support the fine-tuning, deployment, and management of AI, ML, and Agentic Services; Guiding the strategic direction of the engineering team, with a primary focus on platform reliability, scalability, and maintainability
• Build and oversee robust systems that empower our customers to optimize and personalize AI and Agents to their specific needs
• You will lead a growing team of engineers focused on building reliable, scalable AI & ML infrastructure and pipelines that power intelligent features across our platform
• You'll partner closely with data scientists, product managers, and platform engineers to transform AI ideas into production-grade, secure, and efficient systems
• As the founding Engineering leader of AI Foundations team, this is a high-impact role that sits at the intersection of artificial intelligence and software delivery – ideal for someone passionate about pushing the boundaries of developer productivity and intelligent automation
• Lead and scale a team responsible for AIOps, including model deployment, monitoring, and lifecycle management
• Architect and implement AI/ML pipelines that are scalable, observable, and reproducible
• Collaborate with cross-functional teams (data science, DevOps, product) to integrate AI/ML systems into our SaaS platform
• Establish best practices for AI/ML experimentation, CI/CD for models, data versioning, and model governance
• Own the full stack of AIOps infrastructure, from data ingestion to real-time inference systems
• Drive technical vision and roadmap for ML platform development
• Act as a mentor and coach, helping engineers grow in a fast-paced, startup environment
• Manage a team of 5+
• Ability to launch new platforms 0 - 1 and drive adoption internally and externally with partner teams