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Priceline CTO Sejal Amin Shifts Focus: Engineers Must Now ‘Hold a Room and a Roadmap’ in AI Era
In a rapidly evolving tech landscape, Priceline’s Chief Technology Officer, Sejal Amin, is redefining what it means to be an effective software engineer. As artificial intelligence reshapes the industry, Amin is prioritizing engineers who can not only write code but also lead teams, communicate vision, and navigate the complexities of modern product development. Her approach reflects a broader industry trend: the growing importance of soft skills, leadership, and strategic thinking alongside technical prowess.
Amin, who leads technology strategy, engineering, and product infrastructure at one of the world’s largest online travel platforms, recently discussed these shifts in an interview with InformationWeek. She emphasized that in the AI era, the ability to “hold a room and a roadmap” — to articulate technical vision, inspire teams, and drive product ownership — is as critical as coding ability. This shift comes as Priceline transitions from a functionally organized structure to a product-centric model, aimed at accelerating delivery and fostering innovation.
For Amin, the transformation is not just about adopting new tools but about cultivating a culture that balances speed with responsibility. “We’re investing heavily in technical leaders, not just technical contributors,” she said. This focus on leadership and collaboration is particularly relevant as AI tools accelerate development cycles, creating both opportunities and challenges for engineering teams.
Why Leadership and Communication Are Now Non-Negotiable
Sejal Amin’s emphasis on leadership and communication skills marks a significant pivot for many tech organizations. Traditionally, engineering roles have been evaluated based on metrics like lines of code written, bug fixes, or deployment frequency. However, as AI tools automate coding tasks and streamline workflows, the industry is recalibrating what it means to measure success.
According to recent industry reports, AI adoption in software development has led to faster deployment cycles but also introduced new challenges, such as increased incidents and rework. A 2026 benchmark report from Cortex found that while engineering velocity has improved, teams must now focus on integrating AI tools responsibly and maintaining code quality. Amin’s approach aligns with this trend, emphasizing the need for engineers to not only leverage AI but also to understand its impact on workflows, governance, and team dynamics.
“AI accelerates development significantly, but speed isn’t the goal on its own,” Amin said. “It needs to be integrated into our workflow. This isn’t just a technical shift; it’s a cultural shift.”
Priceline’s Shift to a Product Operating Model
When Amin joined Priceline in 2024, she identified a critical need to modernize the company’s organizational structure. The company had been operating with a functional model, where teams were siloed by expertise — such as front-end, back-end, or data science. While this approach fostered deep technical skills, it also created bottlenecks and slowed down product delivery.
In response, Amin spearheaded a transition to a product operating model. This shift involved restructuring teams around products and services, rather than functions. The goal was to create cross-functional units that could own end-to-end delivery, from conception to deployment. “When a team knows what products and services they manage, it creates a really strong sense of ownership and accountability,” Amin explained.
This change has had a measurable impact. Priceline has reported faster delivery cycles and tighter feedback loops between development and learning. The transition also reduced resistance within the organization, as teams embraced the shift toward greater collaboration and shared responsibility.
AI and the Future of Engineering Metrics
Amin’s focus on leadership and communication is particularly relevant in the context of AI. As generative AI tools become more prevalent, they are changing the way engineers function. For example, a 2025 report from DevOps Research and Assessment (DORA) found that AI amplifies both strengths and weaknesses in engineering organizations. Teams that are already strong in collaboration and governance see greater benefits from AI adoption, while those with siloed structures struggle to integrate the tools effectively.
At Priceline, Amin is ensuring that AI adoption is accompanied by robust governance policies and training programs. She is also rethinking how the company measures engineering effectiveness. “We have to create space for innovation and for people to think about what it means to their work,” she said. This includes tracking metrics like code quality, team collaboration, and the ability to adapt to new tools — not just raw output.
For Amin, the future of engineering is not just about writing code faster but about building a culture that values ownership, communication, and strategic thinking. “We’re seeing enthusiasm from everywhere, not just engineers, but across the organization,” she said. “That creates opportunities, but we also need to focus on how to use tools and channel all of that energy more responsibly.”
Key Takeaways
- Leadership and communication are now critical skills for engineers. Sejal Amin is prioritizing engineers who can “hold a room and a roadmap,” meaning they can articulate technical vision and inspire teams.
- Priceline has shifted to a product operating model. This change has improved delivery speed and fostered a culture of ownership and accountability.
- AI adoption requires responsible integration. While AI accelerates development, teams must focus on governance, code quality, and collaboration to avoid pitfalls like increased incidents and rework.
- Engineering metrics are evolving. Companies are now measuring success based on factors like team collaboration, adaptability, and the ability to integrate new tools.
- Cultural change is as important as technical change. Amin emphasizes the need for organizations to create space for innovation and responsible tool use.
What’s Next for Priceline and the Industry
As AI continues to reshape the tech industry, Priceline’s approach offers a roadmap for other organizations looking to modernize their engineering cultures. Amin’s focus on leadership, communication, and responsible AI adoption reflects broader industry trends, where the ability to navigate complexity and drive collaboration is becoming just as important as technical expertise.
For readers interested in staying updated on these trends, Priceline’s official press center (press.priceline.com) and recent reports from industry leaders like Cortex and DORA provide valuable insights into the future of software engineering.
What are your thoughts on the evolving role of engineers in the AI era? Share your experiences and predictions in the comments below, and don’t forget to share this article with colleagues who are navigating similar challenges.
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