Engineering Manager - Personalization (Hybrid - Seattle)

Nordstrom•Seattle, WA

3d•$166,000 - $258,000•Hybrid

About The Position

Nordstrom is hiring an Engineering Manager to lead the team responsible for its Personalization Engine, including recommendation and styling capabilities across marketing and digital experiences. The platform produces ranked, personalized recommendations at scale using machine learning and generative AI, supporting product recommendations and complete-look outfits, with the ability to extend to other content types. The manager owns delivery, reliability, and team health, and reports to the Senior Director of Engineering supporting Marketing Technology and Personalization. The team partners closely with data science, product, and platform engineering and is adopting an AI-native product development lifecycle organized around Flow and SRE squads. Managers operate as player-coaches, staying close to architecture, code reviews, and incident response while developing the team's planning, building, and shipping practices. This is a hybrid position in Seattle, Washington. Candidates must be available to work at Nordstrom's corporate headquarters at least four days per week.

Requirements

At least 5 years of relevant work experience in software or machine learning engineering.
At least 2 years of experience managing engineering teams, or strong technical-lead experience and readiness to move into people management.
Depth in building and operating production machine learning or recommendation systems at scale, including training pipelines, low-latency model serving, cloud infrastructure, and Kubernetes-based platforms.
A track record of improving reliability, including SLOs, on-call health, incident response, and post-incident learning.
Demonstrated agile delivery discipline, with a team that delivers committed work on committed dates.
Ability to influence without authority and communicate candidly, align product, engineering, and business partners with competing priorities, and raise concerns early with proposed solutions.
BA/BS in Computer Science or a closely related field, or equivalent practical experience.

Nice To Haves

Hands-on experience with Vertex AI or comparable managed machine learning training platforms.
Experience leading an end-to-end migration, such as moving machine learning serving workloads between cloud and in-house platforms.
Background in retail, e-commerce, or marketing technology.
Experience applying generative AI and agentic tooling to engineering workflows or customer experiences.
Familiarity with sequential or transformer-based recommendation approaches.

Responsibilities

Define technical direction for personalization, including how behavioral and product signals become ranked recommendations and complete-look outfits across Nordstrom's marketing and digital experiences.
Build alignment with product, data science, and platform teams to implement the technical direction.
Lead, develop, and support engineers, giving them ownership and helping them grow into technical leaders.
Own reliability of the high-scale personalization platform supporting Nordstrom and Nordstrom Rack digital properties.
Improve model quality, data quality, and observability so issues are detected before affecting customers or stakeholders.
Guide the team to critically assess technical approaches and prioritize the right problems.
Stay involved in architecture, code reviews, and incident response while advancing AI-native planning, development, and delivery practices.
Establish clear priorities, make delivery commitments, and consistently deliver on committed dates.
Represent the team to business partners and senior leadership, explain technical work in terms of business value, advocate for the team, and develop a vision for expanding its scope and projects.
Communicate openly, share context, and follow through consistently.
Build on the team's existing strengths and culture, set clear expectations, and avoid micromanaging.
Remove blockers, push back constructively on unrealistic scope or timelines, and protect the team from unnecessary churn and pressure.
Support work-life balance and consider how changes to roles, priorities, and processes affect individuals.
Recognize team members' contributions publicly.