AI Engineer

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  "source_hash": "16952e3deb9ffdc1eaa1e427547f35d38679ba4dc54249e6f2aeb86e8df9431a",
  "last_changed_at": "2026-05-31T10:25:42.802Z",
  "active_status": "deleted"
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{
  "language": "en",
  "location": {
    "raw": "Seattle",
    "city": "Seattle",
    "region": "WA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.75
  },
  "salary_max": 220000,
  "salary_min": 110000,
  "inferred_at": "2026-05-29T06:54:30.437Z",
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    "language": "en",
    "location": {
      "raw": "Seattle",
      "city": "Seattle",
      "region": "WA",
      "country": "United States",
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      "confidence": 0.75
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    "countries": [
      "United States"
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  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
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{
  "lists": [
    {
      "text": "What You'll Do",
      "content": "<div>\n<div>\n<p>You may work across several of these areas depending on level and project:</p>\n<p><strong>Build GenAI / LLM applications</strong></p>\n\n<li>Design and develop LLM-powered applications using enterprise AI platforms (e.g., AWS Bedrock, Azure OpenAI / Azure AI platforms, Google Vertex AI).&nbsp;</li>\n<li>Implement multi-step orchestration workflows that translate user intent into reliable actions and explainable outputs.&nbsp;</li>\n<li>Build robust <strong>RAG pipelines</strong> (vector databases, embeddings, chunking strategies) and validate grounding quality.&nbsp;</li>\n\n<p><strong>Engineer agentic solutions (Plan → Reason → Execute → Feedback)</strong></p>\n\n<li>Design agent reasoning/control patterns (e.g., planning vs execution separation, tool calling, memory/context management).</li>\n<li>Integrate agents with tools/APIs and enterprise workflows with appropriate governance and guardrails.&nbsp;</li>\n\n<p><strong>Prompt engineering + evaluation</strong></p>\n\n<li>Create reusable prompt templates/libraries; implement prompt testing frameworks; establish prompt versioning/governance.</li>\n<li>Evaluate solutions for quality/safety/latency/cost and iterate quickly.&nbsp;</li>\n\n<p><strong>Production readiness + operations</strong></p>\n\n<li>Partner with platform/LLMOps teammates to deploy, monitor, and improve LLM systems in production.</li>\n<li>Build observability and reliability mechanisms for agent-based workflows.</li>\n\n<p><strong>Client-facing consulting</strong></p>\n\n<li>Lead technical discovery, map workflows/pain points, and communicate solutions to technical and executive stakeholders.&nbsp;</li>\n\n</div>\n</div>"
    },
    {
      "text": "What We're Looking For (Must-Have)",
      "content": "\n<li><strong>1–2+ years hands-on GenAI / Agentic AI experience building LLM apps</strong> on enterprise platforms (AWS Bedrock / Vertex AI / Azure AI platforms) in a professional setting.</li>\n<li>Strong<strong> backend engineering</strong> experience (Python preferred) delivering production-grade systems.</li>\n<li>Hands on<strong> professional experience</strong> with&nbsp;<strong>RAG</strong> patterns and implementation.&nbsp;</li>\n<li>Ability to communicate clearly and contribute in fast-moving, cross-functional teams.</li>\n<li>Computer Science / strong CS fundamentals&nbsp;</li>\n"
    },
    {
      "text": "Nice-to-Have/Differentiators",
      "content": "<div>\n<div>\n\n<li>Applied Scientist style skills: deep learning/NLP with PyTorch/TensorFlow + Hugging Face; ability to interpret research and implement emerging techniques.</li>\n<li>Fine-tuning and optimization methods (LoRA/PEFT/QLoRA), distillation/quantization/pruning, GPU memory optimization.</li>\n<li>Experience building secure tool integrations / agent middleware (tool schemas, SaaS integrations like Salesforce/SAP/ServiceNow, OAuth2, API security).&nbsp;</li>\n<li>Evaluation harnesses and regression testing for prompts/agents; RAG quality testing.&nbsp;</li>\n<li>Cloud-native experience in large enterprise environments.</li>\n\n</div>\n</div>"
    },
    {
      "text": "",
      "content": "<h3><strong>Levels</strong></h3>\n<p>We’re hiring <strong>across multiple levels</strong> (entry/junior through senior/principal).<br><br></p>\n<h3><strong>How You’ll Work</strong></h3>\n<p>You’ll collaborate in agile delivery pods alongside product, architecture, engineering, and ops roles to build and scale agentic AI solutions. <br>Projects may include discovery workshops, rapid prototyping, and production pilots with measurable outcomes.</p>\n<h3><strong>Apply</strong></h3>\n<p>Send your application (or resume) and include:</p>\n\n<li>1–2 examples of <strong>LLM apps/agentic systems</strong> you built (even internal or side projects)</li>\n<li>The platform(s) you used (e.g., Bedrock / Vertex / Azure) and how you handled <strong>RAG, evaluation, and production concerns</strong>&nbsp;</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1776137330080,
  "updatedAt": null,
  "categories": {
    "team": "Architecture & Engineering",
    "location": "Seattle",
    "commitment": "Full-Time",
    "department": "AI, Data & Technology Services",
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      "Seattle"
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    "max": 220000,
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    "currency": "USD",
    "interval": "per-year-salary"
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