Senior Engineer 2: AI Agentic Platform (hybrid - Seattle, Wa)

Nordstrom Nordstrom · Retail · Seattle, WA

Senior Engineer 2 at Nordstrom to build the core AI Agentic Platform, enabling AI agents to reason, use tools, and take action. Responsibilities include designing and building agent orchestration, tool-use pipelines, and memory systems, integrating LLMs and RAG, and ensuring scalability and observability. Requires strong software engineering experience, AI fluency with LLMs and RAG, and platform engineering experience in AI teams.

What you'd actually do

  1. 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.
  2. Own end-to-end solution design for platform components spanning multiple engineers’ work, with full upstream/downstream integration consideration.
  3. 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.
  4. 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.
  5. Design systems accounting for current and upcoming product cycles, team-level cost responsibility, and alignment with cross-functional roadmaps.

Skills

Required

  • 6+ years of professional software engineering experience
  • designing and delivering complex, scalable distributed systems
  • Hands-on experience working with LLMs
  • foundation model APIs (OpenAI, Anthropic, Google, etc.)
  • prompt engineering
  • retrieval-augmented generation (RAG) architectures
  • embedding-based search in production environments
  • Platform engineering in AI teams
  • built shared AI infrastructure or developer platforms within an AI-focused product organization
  • Proficiency in Python and/or Java
  • strong grasp of multiple tech stacks
  • cloud-native development on AWS and/or GCP
  • Experience with RESTful services
  • event-driven architectures
  • backend databases (SQL, NoSQL, or cloud-native datastores)
  • containerization technologies (Kubernetes, Docker)
  • modern CI/CD practices and tools (e.g., GitLab)
  • design systems spanning multiple weeks or months of work
  • balancing short and long-term trade-offs
  • building observability into systems
  • real-time alerting, dashboards, metrics, and performance accountability
  • Experience working with cross-functional teams
  • Strong verbal and written communication skills
  • Agile development experience
  • 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
  • multi-agent orchestration patterns: task decomposition, tool-use pipelines, short-term and long-term agent memory, and human-in-the-loop workflows
  • agent evaluation frameworks, safety guardrails, and responsible deployment of AI agents in production environments
  • Background in retail, e-commerce, or supply chain domains
  • Experience with big data technologies (Spark, BigQuery, Redshift)
  • 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

What the JD emphasized

  • AI Agentic Platform
  • AI agents
  • reason
  • use tools
  • coordinate across systems
  • take action
  • AI fluency
  • LLM APIs
  • embedding models
  • vector stores
  • RAG patterns
  • agentic frameworks
  • platform scalability
  • observability
  • performance and security
  • AI Agentic systems
  • autonomous agents
  • multi-agent orchestration patterns
  • agent evaluation frameworks
  • safety guardrails
  • responsible deployment of AI agents

Other signals

  • AI Agentic Platform
  • AI agents to autonomously reason, use tools, coordinate across systems, and take action
  • shared foundation
  • platform capabilities