AI Engineer

ALOIS Solutions; Seattle (WA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

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

You’ll own the full lifecycle of an agent’s development from design through production deployment, working from client-scoped requirements and collaborating with engineers and stakeholders to deliver robust, scalable

Qualifications

• 5+ years of software engineering with production-grade code and full SDLC ownership.
• Recent hands-on experience shipping agentic systems, not just experiments.
• Working knowledge of modern foundation models and agent design trade-offs.
• Experience with programmatic evaluation, metrics, and failure-mode analysis.
• Experience with retrieval, context assembly, and memory/state under real constraints.
• Framework-agnostic, with exposure to listed AI tooling as transferable concepts.
• Strong written and verbal communication; able to work from client-defined requirements.

Responsibilities

• Design and build production agents and multi-agent orchestration systems.
• Evaluate agentic systems with metrics, offline/online tests, and failure analyses.
• Handle context engineering: memory, context handling, and efficiency constraints.
• Deliver production-ready code through the full SDLC with minimal hand-holding.
• Collaborate with client engineers and stakeholders to align with requirements.
• Help raise the team’s fluency with generative AI via practical guidance.
• Contribute to engineering standards and best practices within the team.

Skills

Software Engineering

Generative AI

Foundation Models

Evaluation

Context Engineering

Frameworks

Communication

Tools

LangGraph

AutoGen

CrewAI

Semantic Kernel

Claude Agent SDK

OpenAI Assistants API

Job description

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.
• 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.