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Vice President, Engineering

Remote, US

About The Princeton Review 

The Princeton Review is a leading tutoring, test prep, and college admission services company. Every year, it helps millions of college- and graduate school–bound students achieve their education and career goals through online and in-person courses delivered by a network of more than 4,000 teachers and tutors, online resources, and its more than 150 print and digital books published by Penguin Random House. The company’s Tutor.com brand is one of the largest online tutoring services in the U.S. It comprises a community of thousands of tutors who have delivered more than 22 million one-to-one tutoring sessions. The Princeton Review is headquartered in New York, NY. Follow the company on LinkedInYouTube and Instagram

 

About the Position 

The VP of Engineering is a senior leadership role with broad scope across engineering, QA, and data, with deep involvement in infrastructure, and security strategy. Reporting to the Chief Product & Technology Officer, this leader will own the strategy, execution, and organizational health of the full technical organization. 

This is a transformation role. In alignment with ambitious company goals for growth and sustained execution excellence, we are investing in a step-change in how we build and ship product: We are embedding AI-native workflows into how we build, moving toward small, highly leveraged teams that conceive and ship in tight cycles. The VP of Engineering will own that shift — building the engineering culture, practices, and org design that maximize developer productivity and get great product into users' hands faster. 

This is a role for a leader who is comfortable operating at a high altitude — setting direction, communicating clearly to executive and board audiences, and making sound investment decisions — while remaining close enough to the work to develop leaders, drive accountability, and earn credibility with the team. 

What You’ll Do 

[Engineering Execution] 

  • Set and maintain high standards for delivery velocity, quality, and predictability across all engineering teams. 
  • Evolve the processes, practices, and accountability systems that enable consistent execution at scale, including CI/CD adoption and a shift-left approach to quality ownership. 
  • Drive the organization’s shift toward modern, cross-functional product teams; partner closely with product leadership to build iterative, collaborative ways of working with rapid feedback loops. Openly and deliberately experiment with new models of teaming and collaboration. Model and set the tone for strong partnership at the Technology Leadership level. 

[Technology Strategy and Platform Health] 

  • Own the 6–24 month technology roadmap: define where we want to be, make the tradeoffs explicit, and work backwards to a credible plan 
  • Provide architectural vision and oversight across the organization; ensure engineering investments align with long-term business goals 
  • Partner closely on infrastructure and security strategy, ensuring the long-term sustainability and resilience of our systems 
  • Make ongoing sound investment decisions around technical debt, platform modernization, and operational resilience. Drive critical modernization efforts by assessing the current state of our systems, setting a clear point of view on what needs to change, and sequencing the investment in a way that appropriately assesses delivery trade-offs.  

[AI Products and Development Practices] 

  • Lead development of AI-powered products in partnership with product and data teams. Own the technical vision and execution, making principled architectural decisions about model selection, RAG pipelines, and build-vs-integrate tradeoffs, and leading the work that turns early-stage experiments into reliable, production-grade products. 
  • Deeply embed AI-based development practices across engineering to improve team capability and throughput. Help us move swiftly and intentionally to agent-assisted coding as a standard part of how our engineers work.  
  • Stay at the leading edge of AI tooling and development practices — continuously evaluating what's emerging, running deliberate experiments in collaboration with product, and advocating clearly for what we should adopt, pilot, or watch. Translate that knowledge into concrete recommendations and decisive action that drives real behavior change. 

 

[Data Platform and Analytics] 

  • Provide strategic oversight and direction for the data team — helping the team set the vision for the data platform and capabilities the product and AI agenda require, including analytics that close the loop on product decisions, ML/AI pipeline infrastructure, and data governance practices. 
  • Partner with business stakeholders to ensure data is a reliable, well-governed foundation for product decisions and operational insight, and also serves functions’ analytics and business process needs throughout the enterprise. 

[Team and Org Development] 

  • Assess, develop, and grow the engineering organization; build the management layer and career paths that will scale the team through the next phase 
  • Develop and mentor leaders across the organization; build a culture where engineers do their best work, are recognized for it, and grow. Make sound decisions about where to invest in internal development vs. external hiring. 
  • Serve as a core member of the technology leadership team, contributing to the strategic direction of the overall technology organization and ensuring the systems, processes, and ways of working are in place for the full technology organization to operate effectively. 
  • Serve as the engineering voice for the executive level; own the narrative on engineering strategy, roadmap, risk, and tradeoffs for the executive team and board audiences 
  • Build strong working relationships with product, content, and business stakeholders; translate technical context into business terms clearly and consistently for non-technical audiences. 

Who You Are 

  • 15+ years in software engineering, with significant time in senior engineering leadership (director level and above) 
  • Experience leading organizations that span multiple functions — product engineering, QA, data, and infrastructure 
  • A track record of shipping product, not just managing roadmaps — you know what great execution looks like and how to build the conditions for it 
  • Deep experience building AI-powered products, leading teams that do, and embedding AI tooling into engineering workflows 
  • Fluency in agile and product engineering principles, and the ability to coach and model them across an organization 
  • Strong executive communication skills; comfortable presenting roadmaps, tradeoffs, and risk narratives to senior leadership and boards 
  • Strong people instincts — you develop leaders, hold the bar on performance and culture, and know how to manage effectively through existing leaders and teams 
  • A natural collaborator who builds trust across functions and levels — you get things done through relationships, not just authority, and you make the people and teams around you better. 
  • Comfortable operating in a mid-sized company where leaders are close to the work and expected to lead from the front 

The Princeton Review and Tutor.com offer a competitive salary which commensurates with experience and skills. 

US Pay Range

$220,000 - $250,000 USD

The Princeton Review is an equal employment opportunity employer. The Princeton Review’s policy is not to discriminate against any applicant or employee based on, and all qualified applicants will receive consideration for employment without regard to, race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, marital status, disability, military status, genetic information, or any other basis protected by applicable law. The Princeton Review also prohibits harassment of applicants or employees based on any of these protected categories. It is also The Princeton Review’s policy to comply with all applicable laws respecting consideration of unemployment status in making hiring decisions.

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