Senior 2 Technical Program Manager, AI Native Operating Model - HYBRID (Seattle, WA)

Nordstrom•Seattle, WA

1d•$166,000 - $258,000•Hybrid

About The Position

Nordstrom Technology is moving to an AI Native operating model, and we're rebuilding the processes, tools, and standards our engineering teams use to build and ship software — without sacrificing quality or stability as speed increases. We need a Senior 2 Technical Program Manager to bring order and rigor to this transformation while it's still taking shape: someone who can turn a direction that's aligned but not yet fully defined into working processes, clear metrics, and day-to-day discipline that both leadership and engineering teams can rely on. This is a senior, individual-contributor role. You'll partner closely with engineering and business leaders as we evolve how engineering teams work — sequencing process changes, building the metrics and reporting that make progress visible, and helping teams adopt new ways of working while some specifics are still being resolved. It's a delivery-focused role: you're measured by what gets built, adopted, and running well. Once a phase is delivered and operating on its own, you'll move to the next priority that needs the same focus. You'll be part of the Technology Portfolio & Operations team, working closely with engineering leaders and cross-functional partners across the business. Success in this role looks less like any single deliverable and more like engineering teams operating with rigor and metrics that leadership can trust as new practices take hold.

Requirements

Bachelor's or Master's degree in Business, Computer Science, Engineering, or related field; will accept any suitable combination of education, experience, and training
10+ years of experience in technical program management with a proven track record leading large-scale, high-impact, cross-functional programs
Demonstrated experience leading teams through significant process transformation, including periods where the plan itself was still evolving
Experience helping engineering teams adopt AI-assisted development tools and practices, and turning that adoption into measurable, durable process change
A demonstrated bias for execution: a track record of delivering defined phases of work to completion, then moving on to the next priority that needs the same focus
A strong track record building measurement approaches and operational reporting that hold up under scrutiny and that leadership can act on
Comfort making sound decisions and sustaining progress while open items are still being resolved
Excellent communication and stakeholder management skills, with the ability to build agreement and influence outcomes without formal authority
Experience mentoring program managers and other cross-functional collaborators, and building organizational capability
Strong analytical and quantitative skills, comfortable using data to back up decisions and recommendations
Familiarity with modern software delivery practices (for example, CI/CD, release management, observability) sufficient to be credible with engineering partners; this is not a hands-on engineering role
Experience leading organizational change management for technology or process transformations
Experience with both waterfall and agile delivery models
Familiarity with portfolio management and collaboration tools

Nice To Haves

Background in retail or technology operations environments
Experience with large-scale technology modernization or transformation initiatives

Responsibilities

Own the day-to-day sequencing of how we roll out new processes and practices under the modern engineering operating model, translating a direction that's aligned in principle but not yet fully specified into concrete plans and checkpoints
Make sound judgment calls on open items, such as thresholds and process ownership, as they get resolved, rather than waiting for total clarity before making progress
Adjust plans as the model itself evolves, and communicate those changes clearly so teams aren't caught off guard
Pilot new processes with a small set of teams first, gather feedback, and refine before rolling out more broadly
Drive change management for the operating model itself, communications, training, and adoption tracking, as its own deliverable
Partner with leadership to define and stand-up key metrics and reporting structure that provide leadership visibility into how the transformation is progressing
Translate qualitative goals, such as moving faster or reducing risk, into concrete, trackable measures that teams can be held to
Build the operational cadence, reviews, checkpoints, escalation paths, and reporting rhythms, that make the new way of working durable rather than a one-time push
Track engineering delivery metrics, such as deployment frequency, lead time for change, change failure rate, and mean time to restore, alongside AI-adoption and process-health indicators
Partner with engineering and business leaders to align on priorities and sequence trade-offs, building consensus without formal authority
Be a clear, credible voice with senior leadership on status, risk, and decisions, and with individual teams on what's happening in practice
Communicate clearly about why our processes are evolving, and help teams adopt new practices with confidence
Anticipate risks and bottlenecks early, and coordinate across teams to manage dependencies that cross organizational boundaries
Track and escalate systemic issues before they become bigger problems
Weigh security, compliance, and platform constraints against delivery speed and team capacity
Map dependencies across the engineering toolchain, source control, CI/CD, ticketing, and observability platforms, to spot cross-system ripple effects
Mentor other program managers and cross-functional partners supporting the transformation, helping them build both planning skills and the judgment to operate effectively through ambiguity