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

Nordstrom Nordstrom · Retail · Seattle, WA

Software Engineer 2 role focused on building and integrating AI agentic solutions for a retail company. Responsibilities include designing and developing agentic components, context engineering, integrating LLM APIs and vector stores, and implementing evaluations and guardrails. Requires AI fluency with LLMs and experience with agentic workflows.

What you'd actually do

  1. 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.
  2. Contribute to context engineering work: helping determine what an agent sees, when, and why, within token, latency, and cost constraints.
  3. 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.
  4. 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.
  5. 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.

Skills

Required

  • 2+ years of professional software engineering experience
  • Hands-on experience working with LLMs or foundation model APIs (OpenAI, Anthropic, Google, etc.)
  • Prompt engineering or retrieval-augmented generation (RAG) patterns
  • Building or contributing to AI agents or agentic workflows (tool-use, orchestration, or integration)
  • Assembling and structuring context for agents within token, latency, and cost constraints
  • Evaluation or testing practices for LLM-based systems (offline benchmarks or basic production monitoring)
  • Solid CS fundamentals (data structures, algorithms, object-oriented design)
  • Production-grade tech stack
  • Working knowledge of cloud-native development on AWS and/or GCP
  • Familiarity with modern agentic frameworks (LangGraph, CrewAI, Semantic Kernel, Claude Agent SDK, OpenAI Assistants API)
  • Strong verbal and written communication skills

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

What the JD emphasized

  • AI Fluency — Required
  • Hands-on experience working with LLMs or foundation model APIs
  • Some experience building or contributing to AI agents or agentic workflows
  • Growing understanding of how to assemble and structure context for agents
  • exposure to evaluation or testing practices for LLM-based systems

Other signals

  • Building agentic solutions end-to-end
  • Integrating LLM APIs, embedding models, vector stores
  • Developing evaluations and guardrails for AI agents