Own: Technical roadmap and execution for our Data and AI products
Own: Strategic objectives for the implementation and adoption of AI and Data driven initiatives across NYPL
Own: Hiring, training, coaching and management of engineering team members
Teach: How to develop and implement data and AI strategies that directly support measurable business outcomes
Teach: Critical and strategic thinking skills, cross-functional collaboration, and technical decision-making abilities to scale the team's impact.
Teach: Champion the ethical and responsible use of AI and data, including bias mitigation, transparency, and the potential impact on patrons and society
Learn: NYPL culture, goals, strategy and the environment in which we work
Improve: Remove roadblocks and advocate for the changes needed to maintain a world-class engineering team
Improve: Help NYPL embrace data-driven transformation and help the organization better leverage data in its business practices
Improve: Ensure that the team’s time and capacity are adequately allocated in order to deliver on high-priority projects in a timely manner
Improve: Socialize core engineering metrics so that the organization better understands Engineering’s internal objectives and results
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.

Requirements

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.
Strong technical understanding of AI/ML DevOps, evaluation frameworks, agentic workflows, and permission systems integration.
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.

Benefits

Be **Helpful** to patrons and colleagues
Be **Resourceful** in solving problems
Be **Curious** in all aspects of your work
Be **Welcoming** and **Inclusive**
Office environment
Hybrid work environment; required work in the office in NYC 3 days a week
Non-Union
Exempt status
Monday - Friday; 9-5

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringsoftware engineeringmachine learning engineeringAI methodologiesNLPSQLNoSQLcloud data warehousingDevOpsinfrastructure as code

Soft Skills

leadershipcoachingstrategic thinkingcross-functional collaborationtechnical decision-makingadvocacycontinuous improvementcommunicationproblem-solvingteam management