In A Nutshell
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).