Software Engineering Manager, Research

The New York Public Library•New York, NY

16d•$150,000 - $155,000•Hybrid

About The Position

NYPL is hiring a Software Engineering Manager to help lead our research teams in developing our suite of discovery and access tools. These include the Research Catalog, which provides access to over 20 million volumes and Digital Collections, which provides access to over a million digitized assets, as well as other tools that provide access to NYPL’s extensive archives and special collections. These patron-facing applications are backed by a set of data pipelines and APIs that support discovery and ensure that patrons can request materials, make research appointments and order high-resolution scans, among other options. This role will ensure that these systems are maintained while helping lead strategic work that will help NYPL build a unified experience for our research patrons, ensuring that they have easy access to the incredible wealth of NYPL’s collections. The Software Engineering Manager will manage 2 high performing teams of engineers that develop and maintain these tools, working to both continue their work and level them up in terms of skills and practices. Additionally this role will contribute to the technical leadership of NYPL Digital by helping set standards for best practices in development and other technical areas. It will be a key member of our engineering leadership and help ensure that our strategic priorities are well defined, deliverable and in line with the teams’ work. They will have the opportunity to partner with departments across NYPL to identify and deliver on shared priorities, helping continue NYPL’s position as a leader in library technology.

Requirements

Bachelor’s Degree -OR- Equivalent 7 - 10 + years of hands-on development experience on relevant tech stack
At least 3 - 5 + years experience managing one or more engineering teams
Strong leadership, mentoring, coaching and decision-making skills
Excellent written and verbal communication skills
Demonstrated ability to level up individual engineers and engineering teams
Hands-on familiarity with modern AI coding assistants and agentic development tools (e.g., Claude Code, GitHub Copilot, Cursor, or comparable), and a point of view on where they help and where they don't
Track record of leading major technical initiatives to solve complex technical problems
Knowledge of non-technical strategies for solving team, culture and process problems
Experience establishing documentation standards and practices
Expertise in Python application development and system design, including production experience with Python web frameworks
Expertise in data pipeline architecture, data stores, queue processing and other tools
Strong understanding of system architecture and design patterns as well as cloud infrastructure (AWS, GCP, etc)
Strong understanding of DevOps practices and their impacts on technical delivery
Strong problem-solving skills and ability to navigate through ambiguity and drive results.

Nice To Haves

Gain an understanding of library science practices, especially around the metadata standards and practices used in NYPL’s Research systems
Investigate the connections between NYPL’s different research tools to learn how records and metadata can be shared and connected between them
Collaborate with Engineering leadership to help improve NYPL Digital’s culture and implement best practices is software development
Grow as a team member, collaborating with other NYPL engineers to solve problems
Retire legacy applications and replace them with modern, streamlined solutions
Identify hidden connections between our collections and design ways to surface them

Responsibilities

Manage the work and output of 6-8 engineers across NYPL’s Research teams communicating priorities and system requirements clearly
Collaborate with the Research teams to build innovative and forward-looking applications for our patrons and staff
Work with product and project leadership to estimate the feasibility and complexity of new products and features
Hire, mentor and coach engineers on best practices and career growth
Foster a psychologically safe team environment — be transparent about challenges, failures, and successes, and encourage staff to ask questions, voice concerns, and engage critically with the work.
Research and recommend solutions driven by data and cost-benefit analysis, with an emphasis on automation and efficiency.
Encourage and enable engineers to adopt AI coding tools and agentic workflows where they improve quality, velocity, or developer experience, while maintaining strong code review, testing, and security practice.
Support team of 6-8 engineers in their day-to-day work
Coach team members on both hard and soft skills
Provide feedback on team performance and motivate team to deliver on project goals
Keep team accountable and ensure delivery