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About This Role
Job Description
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About the Team and the Role
Nordstrom is investing in AI as a core driver of retail innovation, and the AI Agentic Platform team is building the shared foundation that makes it possible. Our platform enables AI agents to autonomously reason, use tools, coordinate across systems, and take action on behalf of customers and business teams — powering experiences across commerce, personalization, inventory, and customer service.
As a Senior Engineer 2, you are a lead individual contributor responsible for the quality of a team’s work and capable of tackling complex design and problem solving without supervision. You will design systems spanning multiple weeks or months of work, make technical decisions that balance short and long\-term business objectives, and take ownership of team\-level costs and metrics. You will champion new techniques, mentor junior engineers, and be a key technical voice in cross\-functional discussions.
A Day in the Life
- Design and build core AI Agentic Platform capabilities — including agent orchestration layers, tool\-use pipelines, memory systems, and APIs that enable product teams across Nordstrom to deploy AI agents.
- Own end\-to\-end solution design for platform components spanning multiple engineers’ work, with full upstream/downstream integration consideration.
- Apply AI fluency to integrate LLM APIs, embedding models, vector stores, and RAG patterns into platform services; evaluate and adopt emerging agentic frameworks as appropriate.
- Make and clearly articulate technical trade\-offs between short\-term delivery needs and long\-term platform scalability, factoring in design, component choice, and infrastructure costs.
- Design systems accounting for current and upcoming product cycles, team\-level cost responsibility, and alignment with cross\-functional roadmaps.
- Lead design and code reviews across the team; provide actionable feedback and maintain a high bar for quality, testability, and extensibility.
- Design key metrics, events, and observability patterns for platform components; drive accountability for performance and security of feature work.
- Work with business, infrastructure, and security teams to deliver enhancements, reliability improvements, and bug fixes for production AI systems.
- Surface potential design or delivery conflicts in the current or upcoming product cycle and make clear recommendations on the best path forward.
- Mentor and support junior engineers across a wide spectrum of technical activities; participate in hiring interviews with clear, specific feedback.
- Ensure own work and team members’ work follows Nordstrom’s engineering and security standards; contribute to those standards.
You Own This If You Have…
Must Have
- 6\+ years of professional software engineering experience, with a strong track record of designing and delivering complex, scalable distributed systems.
- AI Fluency — Required: Hands\-on experience working with LLMs, foundation model APIs (OpenAI, Anthropic, Google, etc.), prompt engineering, retrieval\-augmented generation (RAG) architectures, and embedding\-based search in production environments.
- Platform engineering in AI teams — You have contributed to or built shared AI infrastructure or developer platforms within an AI\-focused product organization, enabling other teams to build reliable AI\-powered features on top of your foundation.
- Proficiency in Python and/or Java; strong grasp of multiple tech stacks and cloud\-native development on AWS and/or GCP.
- Experience with RESTful services, event\-driven architectures, and backend databases (SQL, NoSQL, or cloud\-native datastores).
- Familiarity with containerization technologies (Kubernetes, Docker) and modern CI/CD practices and tools (e.g., GitLab).
- Demonstrated ability to design systems spanning multiple weeks or months of work, incorporating a full team’s worth of engineers, and balancing short and long\-term trade\-offs.
- Strong emphasis on building observability into systems — real\-time alerting, dashboards, metrics, and performance accountability.
- Experience working with cross\-functional teams including product, business, infrastructure, and security stakeholders.
- Strong verbal and written communication skills; ability to articulate complex technical decisions to both technical and non\-technical audiences.
- Agile development experience (Scrum, Kanban, Lean, or similar) with a continuous improvement and quality mindset.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
Nice to Have
- Hands\-on experience building AI Agentic systems — designing or deploying autonomous agents using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or OpenAI Assistants API.
- Familiarity with multi\-agent orchestration patterns: task decomposition, tool\-use pipelines, short\-term and long\-term agent memory, and human\-in\-the\-loop workflows.
- Experience with agent evaluation frameworks, safety guardrails, and responsible deployment of AI agents in production environments.
- Background in retail, e\-commerce, or supply chain domains — understanding of how AI agents can drive value in inventory, fulfillment, personalization, or customer service.
- Experience with big data technologies (Spark, BigQuery, Redshift) and integrating ML models into production platform services.
- Contributions to open\-source AI or platform projects; curiosity and 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.
$166,000\.00 \- $258,000\.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\_17\-19\.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 $166K-$258K range is above the median for AI Agent Developer roles in our dataset (median: $192K across 41 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 3,823 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 $245,040 based on 106 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($212K) sits 13% below the category median. Disclosed range: $166K to $258K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Nordstrom AI Hiring
Nordstrom has 1 open AI role right now. They're hiring across AI Agent Developer. Based in Seattle, WA, US. Compensation range: $258K - $258K.
Location Context
AI roles in Seattle pay a median of $227,400 across 1,084 tracked positions. That's 14% 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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.
Frequently Asked Questions
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