Director of Software Engineering (AI and Data)

Department: Digital

Employment Type: Full Time

Location: Stephen A. Schwarzman Building

Reporting To: Garvita Kapur

Compensation: $160,000 - $185,000 / year

Description

This is not a remote position; this role requires onsite work in NYC office 3 days a week.

Overview
The New York Public Library has been an essential provider of free books, information, ideas, and education for all New Yorkers for over 125 years. Founded in 1895, NYPL is the nation's largest neighborhood public library system and the most used research library in the world. NYPL provides a fundamental resource to millions of readers, learners and scholars. The Library’s portfolio of digital products and platforms is the core linchpin in how our patrons near and far can access information to create new content, support their personal learning and build stronger communities.  The New York Public Library (NYPL) is seeking an inspiring and technically adept Director of Engineering, Data and AI to lead our data and artificial intelligence initiatives. This critical role is 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. Our core objective is to develop and deploy these powerful tools in a responsible and ethical manner. This role’s goal is to empower researchers, scholars, and the general public to unearth and engage with materials within NYPL's vast and diverse collections in impactful ways. It will also seek to improve these discovery processes via the robust collection and management of data, furthering NYPL’s ability to understand its patrons and improve its offerings to them.

We are looking for someone we can count on to:Own:

• Technical roadmap and execution for our Data and AI products
• Strategic objectives for the implementation and adoption of AI and Data driven initiatives across NYPL
• Hiring, training, coaching and management of engineering team members
• Continuous improvement of Engineering practices
• Our tech stacks, frameworks, vendor tools, and processes
• Identification and mitigation of risk

Teach:

• How to develop and implement data and AI strategies that directly support measurable business outcomes
• Critical and strategic thinking skills, cross-functional collaboration, and technical decision-making abilities to scale the team's impact.
• Champion the ethical and responsible use of AI and data, including bias mitigation, transparency, and the potential impact on patrons and society
• New technologies, such as AI-enabled engineering tools to improve workflows and data management tools 

Learn:

• NYPL culture, goals, strategy and the environment in which we work
• The specific challenges that digital technology introduces for our staff, patrons, vendors, partners and the Library as a whole
• Stay up to date on the latest developments in AI/ML technology, as well as ongoing developments in data management technologies and platforms

Improve:

• Remove roadblocks and advocate for the changes needed to maintain a world-class engineering team
• Help NYPL embrace data-driven transformation and help the organization better leverage data in its business practices
• Ensure that the team’s time and capacity are adequately allocated in order to deliver on high-priority projects in a timely manner
• Socialize core engineering metrics so that the organization better understands Engineering’s internal objectives and results 
• Break down silos between individual engineers, and between engineering teams and key partners.  

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.