Engineer 1: Agentic AI - Inventory Solutions (Hybrid - Seattle, WA)

Nordstrom•Seattle, WA

5d•$104,500 - $162,500•Hybrid

About The Position

The Inventory Integration Systems team owns the platforms and data that track in-transit inventory, reconcile audits, capture vendor data, and maintain accurate enterprise inventory across Nordstrom’s multi-market, multi-channel business. The team is applying agentic AI to inventory systems including AURA, IAP, OmniTrace, and the PADLC agent pipeline, developing agents that investigate inventory problems, correlate signals, and take scoped actions. As an early-career individual contributor, the Engineer 1 builds foundational agentic AI engineering skills on production inventory systems. Under the guidance of senior engineers, the role implements well-scoped agent components, writes tests, and learns how production agentic systems are designed, evaluated, and operated. The position collaborates with engineering, product, and business stakeholders to support inventory platforms and reduce manual audit and reconciliation effort.

Requirements

At least 1 year of professional software engineering experience, including internships, or a relevant certification such as a bootcamp.
Some hands-on exposure to LLMs or foundation model APIs, through coursework, projects, internships, or professional experience.
Curiosity about agentic AI, including how agents use tools, retrieve context, and take actions, and a desire to build production skills in this area.
Solid computer science fundamentals, including data structures, algorithms, and object-oriented design.
Familiarity with RESTful APIs, JSON, and service communication.
Basic understanding of software testing practices and version control such as Git.
Strong verbal and written communication skills and a collaborative, feedback-seeking mindset.
Willingness to learn modern agentic frameworks such as LangGraph, CrewAI, Semantic Kernel, or the Claude Agent SDK.

Nice To Haves

Coursework, personal projects, or internship experience involving prompt engineering, retrieval-augmented generation, or vector databases.
Exposure to a backend language and framework such as Java/Spring Boot or Python, and messaging middleware such as Kafka.
Exposure to cloud platforms such as AWS or GCP, containerization with Docker or Kubernetes, and CI/CD basics.
Familiarity with backend databases such as Spanner or Postgres.
Interest or coursework in retail, e-commerce, supply chain, or inventory.
Contributions to open-source AI projects or personal experimentation with LLM applications.

Responsibilities

Implement components of agentic inventory solutions, including tool integrations, prompt templates, and retrieval steps, under senior engineers’ direction.
Write clean, well-tested code and clearly document work.
Learn and apply context engineering to ground agents in inventory context such as audit records, ledger state, and vendor data.
Help build and run evaluation scripts and offline benchmarks to assess agent safety, accuracy, and reliability.
Participate in on-call rotations and design reviews, debug issues, and surface trade-offs related to owned functions or components.
Add basic instrumentation, including logging, metrics, and alerts.
Follow engineering and security standards, including secure handling of sensitive inventory and vendor data.
Collaborate with engineering, product, and business stakeholders to understand the work’s role in the larger inventory platform and identify opportunities to reduce manual audit and reconciliation effort.