Responsible for overseeing the development, and operation of NYPL’s enterprise data platforms and driving the in-house development of cutting-edge AI-powered search and discovery products.

Responsibilities

Technical Strategy and Operation

• Identify, evaluate, and implement emerging technologies, algorithms, and methodologies into our products and services.
• Define and champion the technical vision and roadmap for NYPL’s data platforms, enterprise analytics capabilities, and the AI Search and Discovery products.

Leadership and People Management

• Directly manage and mentor a team of Tech Leads and senior engineers, cultivating their leadership skills, business acumen, and technical decision-making.
• Own the hiring, training, and coaching process for Engineering team members, fostering a culture of innovation and continuous improvement.
• Set clear goals and metrics for software development teams and maintain high standards of software quality while delivering on project goals.

Engineering Practices and Architecture

• Own the continuous improvement of Engineering practices, patterns, and processes, removing roadblocks to maintain a world-class engineering team.
• Evaluate emerging technologies and industry trends (including AI-enabled engineering tools) and incorporate them into the organization’s practices where appropriate.
• Drive the resolution of complex technical challenges and lead efforts to improve engineering processes.

Skillset

• Bachelor’s degree, or equivalent experience/application.
• Minimum of 10+ years of experience in data engineering, software engineering, or machine learning engineering, with at least 3-5 years in a leadership/management role.
  5 -10 years of progressive leadership/management experience.
• Drive continuous improvement in AI methodologies and best practices.
• Demonstrates good judgement in handling situations with multiple good solutions, or situations with no good solution.
• Proactive mindset that solves future problems before they become emergencies.
• Strong technical understanding of AI/ML DevOps, evaluation frameworks, agentic workflows, and permission systems integration. Proven ability to collaborate closely with technical leads and data scientists.
• Deep expertise in designing, building, and operating large-scale, production-grade data platforms and pipelines (SQL/NoSQL, cloud data warehousing like Snowflake, Databricks).
• Production experience in leading an AI/ML engineering team to deliver a product, specifically involving NLP, vector databases, and RAG architectures.
• Production experience working with data stores, including ElasticSearch and/or Solr, with vector databases/stores a plus.
• Deep understanding of software development best practices, including DevOps best practices around CI/CD, git workflows, testing/test automation, and infrastructure as code (IaC).
• Familiarity with cloud infrastructure, with experience on AWS a plus.
• Manages a diverse technology/developer team (2-6 tech leads and engineers).

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