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About This Role
Job Description
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About the Team and the Role
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Nordstrom is investing in AI as a core driver of retail innovation, and the AI Agentic Solutions team is the pillar responsible for taking that investment from idea to impact. We define the “art of the possible” with agents — partnering with business and technology teams to identify where agentic AI can meaningfully change how Nordstrom operates, then designing and building those solutions end\-to\-end across commerce, personalization, inventory, and customer service. Our team sits at the intersection of four disciplines: agent engineering, context engineering, evaluations and guardrails, and memory and state management for agentic solutions.
As an Engineer 2, you are a solid individual contributor with growing ownership over agentic components and features. You're a subject matter expert within your specific piece of the solution, capable of designing the interaction between multiple modules, and comfortable operating with minimal supervision. You'll partner closely with senior engineers to build production agentic workflows and start developing your own point of view on context engineering, evaluations, and agent design.
A Day in the Life
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- Design and build agentic components with minimal supervision — tool\-use integrations, retrieval steps, and orchestration logic — considering how they interact with other modules in the system, writing clear, concise, well\-tested code along the way.
- Contribute to context engineering work: helping determine what an agent sees, when, and why, within token, latency, and cost constraints.
- Apply AI fluency to integrate LLM APIs, embedding models, vector stores, and agentic frameworks into production services, and build the evaluations and guardrails — offline benchmarks and online telemetry — that demonstrate those components are safe, reliable, and accurate.
- Participate in on\-call rotations, using debugging and profiling tools to resolve issues across the team, and contribute to root\-cause analysis on difficult problems.
- Learn to lead work processes and design reviews — including reviewing the work of other engineers — and help teammates think through trade\-offs on the pieces you know best.
- Understand how to log events and publish metrics for the systems you own, and model good practices for access control and sensitive data handling.
- Understand business metrics for the team and how your work connects to the wider AI Agentic Solutions roadmap, partnering with business, infrastructure, and security teams to deliver enhancements and bug fixes for production systems.
You Own This If You Have…
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*Must Have*
- 2\+ years of professional software engineering experience.
- AI Fluency — Required: Hands\-on experience working with LLMs or foundation model APIs (OpenAI, Anthropic, Google, etc.), including some exposure to prompt engineering or retrieval\-augmented generation (RAG) patterns.
- Some experience building or contributing to AI agents or agentic workflows — tool\-use, orchestration, or integration with downstream systems — whether in production, side projects, or coursework.
- Growing understanding of how to assemble and structure context for agents within token, latency, and cost constraints, and exposure to evaluation or testing practices for LLM\-based systems, including offline benchmarks or basic production monitoring.
- Solid CS fundamentals — data structures, algorithms, and object\-oriented design — plus at least one production\-grade tech stack and working knowledge of cloud\-native development on AWS and/or GCP.
- Familiarity with modern agentic frameworks such as LangGraph, CrewAI, Semantic Kernel, the Claude Agent SDK, or OpenAI Assistants API.
- Strong verbal and written communication skills; comfortable explaining technical work to teammates and cross\-functional partners.
*Nice to Have*
- Experience with RESTful services, event\-driven architectures, and backend databases (SQL, NoSQL, or cloud\-native datastores).
- Familiarity with containerization technologies (Kubernetes, Docker) and CI/CD practices.
- Interest in building observability into systems — real\-time alerting, dashboards, and metrics.
- Background or interest in retail, e\-commerce, or supply chain problem spaces.
- Exposure to big data technologies (Spark, BigQuery, Redshift) or integrating ML models into production services.
- Contributions to open\-source AI projects or active engagement with the broader AI/ML engineering community.
Pay Range Details
The pay range(s) below has been provided in compliance with state specific laws. Pay ranges may be different for other locations.
Pay offers are dependent on the location, as well as job\-related knowledge, skills, and experience.
$121,500\.00 \- $188,500\.00 Annual We’ve got you covered…
Our employees are our most important asset and that’s reflected in our benefits. Nordstrom is proud to offer a variety of benefits to support employees and their families, including:
- Medical/Vision, Dental, Retirement and Paid Time Away
- Life Insurance and Disability
- Merchandise Discount and EAP Resources
This position may be eligible for performance\-based incentives/bonuses. Benefits include 401k, medical/vision/dental/life/disability insurance options, PTO accruals, Holidays, and more. Eligibility requirements may apply based on location, job level, classification, and length of employment. Learn more in the Nordstrom Benefits Overview by copying and pasting the following URL into your browser: https://careers.nordstrom.com/pdfs/Ben\_Overview\_16\.pdf A few more important points...
The job posting highlights the most critical responsibilities and requirements of the job. It’s not all\-inclusive. There may be additional duties, responsibilities and qualifications for this job.
For Los Angeles or San Francisco applicants: Nordstrom is required to inform you that we conduct background checks after conditional offer and consider qualified applicants with criminal histories in a manner consistent with legal requirements per Los Angeles, Cal. Muni. Code 189\.04 and the San Francisco Fair Chance Ordinance. For additional state and location specific notices, please refer to the Legal Notices document within the FAQ section of the Nordstrom Careers site.
Applicants with disabilities who require assistance or accommodation should contact the nearest Nordstrom location, which can be identified at www.nordstrom.com.
Please be mindful that there may be legal notices and requirements related to this job posting that are specific to your state. Review the Career Site FAQ’s for relevant information and guidelines.
Current Nordstrom employees: To apply, log into Workday, click the Careers button and then click Find Jobs.
Nordstrom keeps job postings open for at least one day after the posting date.
© 2026 Nordstrom, Inc
Salary Context
This $121K-$188K range is in the lower quartile for AI Agent Developer roles in our dataset (median: $200K across 33 roles with salary data).
View full AI Agent Developer salary data →Role Details
About This Role
AI Agent Developers build autonomous systems that can reason, plan, and take actions. They design multi-step workflows, tool-use frameworks, and orchestration layers that let LLMs interact with external systems. This is the frontier of applied AI engineering.
Agent development is where the most interesting (and hardest) problems in applied AI live right now. Making an LLM answer a question is straightforward. Making it reliably execute a 15-step workflow that involves calling APIs, reading databases, making decisions, and recovering from errors is an unsolved problem. You're building systems that have to work despite the fact that the underlying model is non-deterministic.
Across the 4,317 AI roles we're tracking, AI Agent Developer positions make up 1% of the market. At Nordstrom, this role fits into their broader AI and engineering organization.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
What the Work Looks Like
A typical week includes: designing the action space and tool definitions for a new agent use case, debugging why the agent chose the wrong action sequence on a specific input, building evaluation frameworks that test agent reliability across hundreds of scenarios, optimizing the prompt chain for cost and latency, and implementing safety guardrails to prevent the agent from taking destructive actions. The work is equal parts engineering and empirical science.
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
Skills Required
Deep experience with LLM APIs and agent frameworks (LangChain, CrewAI, AutoGen). Strong understanding of prompt engineering, function calling, and error handling for non-deterministic systems. Python is standard. Experience with orchestration patterns, state management, and workflow engines adds significant value.
The best agent developers think like systems engineers. They design for failure modes, build observability into every step, and understand that agent reliability is the product. Expertise in evaluation methodology for non-deterministic systems is the differentiator. Can you measure whether your agent works 'well enough'? Can you find the edge cases where it breaks?
Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
Compensation Benchmarks
AI Agent Developer roles pay a median of $240,000 based on 96 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($155K) sits 35% below the category median. Disclosed range: $121K to $188K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Nordstrom AI Hiring
Nordstrom has 2 open AI roles right now. They're hiring across AI Agent Developer. Based in Seattle, WA, US. Compensation range: $162K - $188K.
Location Context
AI roles in Seattle pay a median of $228,700 across 516 tracked positions. That's 6% above the national median.
Career Path
Common paths into AI Agent Developer roles include Software Engineer, LLM Engineer, Prompt Engineer.
From here, career progression typically leads toward AI Architect, Principal Engineer, Head of AI Engineering.
Build agents. That's the portfolio. Take an open-source agent framework, build something that completes a non-trivial multi-step task, evaluate it rigorously, and document what you learned about reliability, cost, and failure modes. The field is new enough that practical experience counts for more than credentials.
What to Expect in Interviews
Interviews focus on systems thinking and reliability engineering. Expect questions about agent architecture: how you'd design a multi-step workflow with error recovery, how you'd evaluate agent performance, and how you'd prevent agents from taking destructive actions. Coding exercises often involve building a simple agent with tool use and evaluating its behavior across different scenarios. Discussion of safety and guardrails is increasingly common.
When evaluating opportunities: Look for roles that describe specific agent use cases, mention evaluation methodology, and talk about production deployment. Early-stage companies exploring agents can be exciting, but be prepared for ambiguity. The most valuable roles are at companies that have already shipped a v1 and need to make it reliable.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Agent Developer is one of the newest and fastest-growing AI role categories. The market is early but accelerating as companies move beyond simple chatbots toward AI systems that can take real actions. Compensation is high because the skill set is rare and the business impact is potentially enormous.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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