Director, Data Infrastructure

Successfully led a team in building and shipping production Data and MLOps/LLMOps Infrastructure. Experience leading platform teams at a medium-to-large company. Former data or ML engineer with technical leadership capabilities. Experience with industry-leading Data and AI/ML systems like Databricks, Snowflake, AWS SageMaker, Kubeflow. Proficiency in data pipelines, latency management, and tools like Airflow, Dagster. Experience building highly available systems using Kubernetes, Kafka. Familiarity with modern LLM evaluation, telemetry, and observability platforms (e.g., Langfuse, MLflow, LangGraph). Experience integrating and managing data systems with specialized frameworks like MCP. Exceptional people manager skilled in attracting, developing, and retaining talent. Ability to solicit, synthesize, and incorporate diverse viewpoints into strategic decisions. Track record of delivering complex, large-scale projects in a fast-paced environment. Clear communication of vision, risks, and technical/business aspects to stakeholders. 10+ years of software engineering experience. At least 5+ years in a direct people management role. B.S. degree (or higher) in Computer Science, Engineering, or related technical field (or equivalent experience).

Lead and mentor Data Engineering and MLOps teams. Foster team and career development. Drive technical strategy and vision for the Data and AI/ML platform. Ensure a scalable core data platform that meets business needs. Foster customer-centricity in platform development. Execute complex, large-scale projects with high availability, accuracy, and security. Align business and infrastructure needs. Define clear ownership and prioritization processes. Own the full lifecycle of the team's roadmap. Focus on value realization and cost optimization. Implement robust operational monitoring and governance. Optimize for speed through stability and security. Champion engineering and operational quality. Ensure standardized SDLC practices for auditable and reproducible systems.