Job DescriptionA 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 DetailsThe 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.
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.
