Engineering Manager - Personalization (Hybrid - Seattle)

Nordstrom•Seattle, WA

1d•Hybrid

About The Position

The Engineering Manager for Personalization leads the engineering team responsible for Nordstrom’s Personalization Engine, including recommendation and styling capabilities across marketing and digital experiences. The team builds ranked, personalized recommendations at scale, using machine learning and generative AI to deliver product recommendations and complete-look outfits, with the ability to support additional content types. The manager owns delivery, reliability, and team health, and reports to the Senior Director of Engineering supporting Marketing Technology and Personalization. This is a hands-on player-coach role within Marketing Technology and Personalization. The manager partners closely with data science, product, and platform engineering, staying engaged in architecture, code reviews, and incident response while helping establish AI-native planning, building, and shipping practices. The organization is structuring work around Flow and SRE squads. The position is hybrid in Seattle, Washington, and requires working at Nordstrom’s corporate headquarters at least four days per week. The manager is expected to develop the team, protect its strengths and culture, set technical direction, improve model and data quality, and represent the team to business partners and senior leadership.

Requirements

At least 5 years of relevant 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.
Experience building and operating production machine-learning or recommendation systems at scale, including training pipelines, low-latency model serving, cloud infrastructure, and Kubernetes-based platforms.
Track record of improving reliability through SLOs, on-call health, incident response, and post-incident learning.
Demonstrated agile delivery discipline, with a team that delivers commitments on the committed dates.
Experience influencing without authority and communicating candidly to align product, engineering, and business partners with competing priorities, and raising concerns early with solutions.
BA/BS in Computer Science or a closely related field, or equivalent practical experience.
Availability to work in the Nordstrom corporate headquarters in Seattle at least 4 days per week.

Nice To Haves

Hands-on experience with Vertex AI or a comparable managed machine-learning training platform.
Experience leading an end-to-end migration, such as moving ML 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 are used to produce ranked recommendations and complete-look outfits.
Build alignment with product, data science, and platform teams to deliver the personalization vision.
Lead and develop engineers, support their growth into technical leaders, and invest in their career development.
Own delivery, reliability, and team health for the Personalization Engine and its products.
Maintain the reliability of a high-scale personalization platform serving Nordstrom and Nordstrom Rack digital properties.
Improve model quality, data quality, and observability so issues are identified before they affect customers or stakeholders.
Challenge the team to select effective approaches and focus on the right problems.
Participate in architecture, code reviews, and incident response while developing AI-native planning, building, and shipping practices.
Set clear priorities, commit to delivery dates, and consistently meet commitments.
Represent the team to business partners and senior leadership, explain technical work in terms of value, advocate for the team, and build a vision for expanding its scope and projects.
Communicate openly and share context, particularly when priorities shift or change is expected.
Build on the team’s existing culture and strengths, establish clear expectations, and give team members room to own their work.
Remove blockers, push back constructively on unrealistic scope, timelines, or priorities, and shield the team from unnecessary churn and pressure.
Support work-life balance, account for how changes affect individual team members, recognize work publicly, and follow through consistently.