Principal Engineer, Agentic AI Platform

Nordstrom

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Seattle, WA
Salary
$191,000–$297,000 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $212k
This role $244k
$135k $314k
below market most similar roles pay here above market

This role pays more than 70% of similar roles. Most pay $169,887–$253,812 — the blue band above. At the midpoint, this role pays about $244k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Nordstrom

Nordstrom is a leading American luxury department store chain offering a wide selection of clothing, shoes, accessories, and beauty products through its stores, Nordstrom Rack outlets, and online. Industry: Luxury Department Store Retail

Nordstrom currently has 48 open roles on FindRole.

Listed pay typically runs $166,000–$258,000 across 22 roles with salary data.

Most-posted roles

View all roles at Nordstrom

At a glance

TL;DR · Principal Engineer, Agentic AI Platform

The Principal Engineer - Agentic AI Platform will lead the design, architecture, and development of a foundational platform enabling AI agents to autonomously reason and collaborate across the technology ecosystem. Working within the AI Agentic Platform domain, this role involves establishing design principles, driving cross-team technical strategy, and creating reusable architecture artifacts. Key responsibilities include defining layers for agent orchestration, tool use, memory, and multi-agent coordination while managing platform observability and safety guardrails. The candidate will utilize Python, Java, AWS, and GCP to build distributed systems, microservices, and data pipelines. Technical requirements include deep fluency with LLM APIs, RAG architectures, and embedding-based search, alongside experience with frameworks like LangGraph, AutoGen, and OpenAI Assistants API to solve complex commerce, inventory, and customer experience problems.

What you'll do

  • Design and architect the foundational layers for agent orchestration, tool use, memory, and multi-agent coordination.
  • Translate business goals into platform capabilities that enable autonomous agent workflows across commerce and inventory domains.
  • Lead cross-team design reviews and establish platform engineering standards and reusable architecture artifacts.
  • Evaluate and integrate LLM APIs, vector stores, RAG patterns, and emerging agentic frameworks into production.
  • Drive decisions on platform observability, evaluation, and safety guardrails to ensure reliable agent behavior.
  • Develop hands-on POCs for novel agentic patterns to prove viability and inform broader team adoption.
  • Serve as the primary technical escalation point for complex agentic system issues and significant operational incidents.
  • Mentor and coach engineers across multiple teams to grow technical talent and engineering standards.

What we're looking for

  • Must have 10+ years of professional software engineering experience designing and delivering large-scale distributed platforms.
  • Must have deep hands-on experience with LLMs, foundation model APIs, prompt engineering, RAG architectures, and embedding-based search in production.
  • Must have experience building shared AI infrastructure or developer platforms within an AI-focused product organization.
  • Must have strong proficiency in Python and/or Java with experience in cloud-native development on AWS and/or GCP.
  • Must have expertise architecting complex distributed systems including microservices, event-driven architectures, API gateways, and data pipelines.
  • Must have a strong DevOps foundation in CI/CD, containerization (Kubernetes/Docker), observability, and reliability engineering.
  • Must have a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
  • Hands-on experience building AI Agentic systems using frameworks like LangGraph, AutoGen, or CrewAI (preferred).

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