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Material
Material
1001 – 5000 Darbinieki
H1B vīzas sponsorsKonsultācijasMārketingsSaaS
Material combines behavioral science, data, design, and technology to help global brands improve customer experiences. Its work spans customer feedback, data modernization, brand design, and cloud engineering, using a systems-thinking approach to connect customer insights with digital transformation. The company operates across marketing, consulting, and SaaS, with teams working on customer-centered strategies and technology.
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Vakances uzņēmumā

Senior AI Architect and Context Engineer

Design governed AI agent platforms, context engineering practices, and enterprise architecture for Material’s global brand growth consultancy. Develop reusable AI accelerators and governance systems.

USAmerikas Savienotās ValstisCAKalifornijaNYŅujorkaTXTeksasa
150 000 $ – 180 000 $ / gads
HibrīdiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta inženierisMašīnmācīšanās inženieris
AzureJavaScriptNode.jsPythonSDLCTypeScript

Apraksts

  • Design and maintain MCP server architectures for knowledge and memory, platform API bridges, and event or webhook triggered agents.
  • Create reusable agent skills, system prompts, scoring rubrics, and harness configurations for governed agent types.
  • Write and publish enterprise governance materials, including architecture decision records, security review checklists, tiered governance models, and architecture review templates.
  • Build an enterprise context engineering layer with repository context file standards, templates, and harness engineering patterns.
  • Lead delivery of a governed internal agent platform pilot, covering agent types, governed sessions, scoped tool access, and audit trail validation.
  • Maintain an accelerator solution map covering reusable toolkit patterns, capability gaps, and accelerator specifications.
  • Contribute to Enterprise Knowledge Graph scoping through ontology design, data catalog foundation architecture, and schema governance.
  • Develop SDLC standards and Engineering Operating Model materials, including quality gates, pull request and review standards, Definition of Done and Ready templates, and CI/CD controls.
  • Prepare enterprise architecture leadership materials, including capability maturity maps, technology demand and decision flow dashboards, application and tool portfolio maps, integration maps, and AI readiness scorecards.
  • Act as the main technical liaison between enterprise architecture and service line teams, turning strategic architecture direction into practical engineering guidance.

Prasības

  • At least eight years in software, solutions, or enterprise architecture roles.
  • Demonstrated experience designing and building AI- or LLM-integrated systems, including agent architectures, prompt engineering, RAG pipelines, and tool-use patterns.
  • Strong knowledge of context engineering, including structured prompt design, system prompt writing, knowledge retrieval optimization, and context window management.
  • Experience with at least two of MCP, LangChain or LangGraph, Claude API, OpenAI API, or comparable LLM orchestration frameworks.
  • Proficiency in Python and TypeScript or Node.js; additional programming languages are an advantage.
  • A record of writing governance materials, including architecture decision records, architecture standards, SDLC documentation, and security review frameworks.
  • Experience with Atlassian products such as Confluence and Jira, Azure, GitHub, and Salesforce.
  • Strong technical writing skills, including executive-ready architecture briefs and technical specifications.
  • Hands-on experience with a major agentic AI ecosystem is preferred.
  • Experience in market research, consulting, or insights and analytics is preferred.
  • Experience with knowledge graph design, ontology modeling, or semantic data architectures is preferred.
  • Familiarity with institutional memory and knowledge management platforms, especially internal developer tools that provide organizational context to AI agents, is preferred.
  • Experience with enterprise governance frameworks such as TOGAF, Zachman, or custom tiered models is preferred.

Priekšrocības

  • Opportunities to learn and develop capabilities.
  • Collaborate with talented colleagues across the company and around the world.
  • Contribute to advanced market offerings and global practices.
  • Create experiences and new value with a focus on outcomes and impact.

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