We are hiring AI Engineers to join a strategic agentic AI engagement with a leading specialty retailer. This is a hands-on build role embedded with the client's engineering team, focused on shipping production agentic systems that automate real business workflows.

The role requires designing, building, and evaluating multi-agent systems — from agent orchestration and tool design through evaluation and context management. The right person is comfortable owning the full lifecycle of an agent's development: from design through production deployment, working from requirements the client has already scoped.

What You'll Do

Design and build production agents and multi-agent orchestration systems — not prototypes or one-off experiments.
Apply sound judgment on agentic design trade-offs: orchestration patterns, multi-agent coordination, tool design, and MCP (Model Context Protocol) integration considerations.
Build and run programmatic evaluations for agents: metrics, offline/online evals, and failure-mode analysis.
Apply context engineering practices: context assembly, memory/state management, and context handling under token, latency, and cost constraints.
Ship production-ready code through the full SDLC, working largely independently from requirements the client's team has already defined.
Partner with client engineers and stakeholders; stay cognizant of end-customer and user experience even when requirements are handed off rather than gathered directly.
Contribute to engineering standards and help raise the broader team's working fluency with generative AI by example.

Required Skills & Experience

Software Engineering: 5+ years of experience with strong fundamentals — production-ready code, full SDLC ownership, and real deployment experience, not just development.
Generative AI / Agentic Systems: Recent (within the last year), hands-on experience building and shipping agentic systems — open source or production — beyond experimentation.
Foundation Models: Working knowledge of modern foundation models and current agentic design approaches and trade-offs.
Evaluation: Practical experience with agent evaluation — programmatic metrics, offline/online evaluation, and failure-mode analysis.
Context Engineering: Practical experience with retrieval, context assembly, and memory/state management under real constraints.
Frameworks: Comfortable working framework-agnostic. Exposure to any of LangGraph, AutoGen, CrewAI, Semantic Kernel, Claude Agent SDK, or the OpenAI Assistants API valued as evidence of transferable concepts, not a checklist requirement.
Communication: Strong written and verbal communication; comfortable operating from client-defined requirements with minimal hand-holding.

Nice to Have

Hands-on experience specifically with the Claude Agent SDK.
Experience with LLM cost management and optimization.
Strong stakeholder communication and requirements-translation skills.
Domain experience in Retail or E-commerce — customer journey data, transaction analytics, or similar.

Work Arrangement & Eligibility

Strong preference for candidates based in Seattle, WA, or otherwise located in the Pacific/West Coast time zone; candidates based in Vancouver, BC are explicitly welcome to apply.
Lower preference for fully remote candidates outside the Pacific/West Coast time zone, due to team overlap requirements.

Hybrid arrangements will be considered for strong candidates; periodic on-site travel to Seattle may be required.

ALOIS Solutions

New Jobs

AI Engineer