Sr. Principal Technical Program Manager (Hybrid - Seattle, WA)

Nordstrom•Seattle, WA

21h•Hybrid

About The Position

We are seeking a Technical Program Manager, Principal Sr. to lead Nordstrom’s enterprise initiative on AI-native developer productivity — fundamentally changing how our technical organizations build, operate, and ship software in an era of AI-assisted development. This senior-most individual contributor role sits at the convergence of AI tooling strategy, developer experience, and organizational transformation. You will define what “AI-native” ways of working mean for Nordstrom’s technology organization — and then systematically build the research foundation, strategy, tooling, training, and measurement infrastructure to make them real at scale across technical organizations. This is not a role for managing programs at arm’s length. It is a role for someone who researches the frontier of AI coding tools, incubates ideas hands-on, builds enabling capabilities, drives adoption across the enterprise, and closes the loop with rigorous impact measurement. You will operate with SVP/VP-level visibility, contribute to and implement Nordstrom’s central AI Native WoW initiative, and represent the forefront of how technical talent works at this company.

Requirements

12+ years of experience in Technical Program Management, with at least a portion focused on developer productivity, platform enablement, or AI/ML tooling programs.
Hands-on familiarity with AI coding tools and agentic development workflows — you’ve used them yourself, not just managed teams that did.
Demonstrated ability to translate frontier AI research into practical, scalable organizational programs — from POC through enterprise adoption.
A track record of building training and enablement programs that drove measurable behavior change in technical organizations.
Experience defining productivity metrics and building dashboards or observability frameworks that created accountability and drove action.
Systems-level thinking: ability to hold technical architecture, developer experience, organizational dynamics, and business strategy simultaneously.
Executive presence: experience influencing at the VP/SVP level with clarity, candor, and strong command of tradeoffs.
Bachelor’s degree in Computer Science, Information Technology, Data Science, or equivalent experience required.

Responsibilities

Research & Thought Leadership: Continuously monitor and evaluate the frontier of AI-native developer tooling — including coding agents (e.g., Claude Code), context management strategies (e.g., MCP, RAG over codebases), agentic harnesses, and code generation workflows.
Incubate and prototype emerging ideas through structured experiments, translating cutting-edge techniques into Nordstrom-relevant proof of concepts before recommending broader adoption.
Synthesize research into point-of-view documents and strategy artifacts that inform investment decisions and executive prioritization across the AI, Platform & Data organization.
Represent Nordstrom’s developer productivity perspective in external technology communities, vendor partnerships, and cross-industry forums.
Strategy & Program Design: Define and own the strategy for AI-native developer productivity at Nordstrom — spanning tooling, process redesign, skills development, and organizational enablement.
Author strategy documents that connect the developer productivity vision to business outcomes, platform architecture priorities, and Nordstrom’s broader AI transformation agenda.
Partner with VP and SVP-level technology leaders to shape investment priorities, program charters, and build/partner/buy decisions related to AI developer tooling.
Contribute to Nordstrom’s central AI enablement initiative, ensuring developer productivity strategy aligns with and amplifies enterprise-wide AI adoption efforts.
Tooling & Capability Development: Identify gaps in existing tooling, context infrastructure, or workflow integration that limit developer productivity; drive the build or adoption of capabilities to close those gaps.
Collaborate with platform and engineering teams to design and deliver internal tools, integrations, and infrastructure (e.g., MCP servers, agent scaffolding, IDE integrations) that enable AI-native development practices.
Establish standards and reference architectures for AI-assisted development workflows that engineering teams can adopt with minimal friction.
Training, Enablement & Adoption: Design and develop training materials, playbooks, and self-service resources that equip engineers at all levels to adopt AI-native ways of working.
Facilitate workshops, lunch-and-learns, and structured cohort experiences that build hands-on fluency with AI coding tools and agentic workflows.
Build and activate an internal community of AI-native practitioners who champion adoption, share discoveries, and accelerate peer learning across the engineering organization.
Partner with engineering leadership and HRBPs to embed AI-native practices into onboarding, career development frameworks, and team rituals.
Metrics, Measurement & Impact: Define the measurement framework for AI-native developer productivity — identifying the right leading and lagging indicators across velocity, quality, developer experience, and cost efficiency.
Build and maintain dashboards and observability tooling that make productivity impact visible to both practitioners and senior leadership.
Establish feedback loops between tooling usage, developer experience signals, and business outcomes; use data to continuously refine program strategy and prioritization.
Report program progress and impact to VP/SVP-level stakeholders with clarity, rigor, and actionable recommendations.
Cross-Functional Leadership & Stakeholder Alignment: Build and leverage a broad network across engineering, product, security, legal, and vendor ecosystems to drive alignment and unblock adoption of AI-native practices.
Navigate organizational complexity to influence decisions at senior levels with analytical rigor, transparency, and clear articulation of tradeoffs.
Mentor TPMs and program managers who work adjacent to AI tooling and productivity initiatives; champion a culture of intellectual curiosity and continuous learning.