Senior Architect / AI Context Engineer This role is to be based near one of our offices in New York City, Austin, or Los Angeles. (Hybrid) About Us We drive intelligent growth for ambitious businesses and leading brands. Customer understanding is more potent and drives greater value when insights go to work directly within marketing and experience priorities. To give our clients that advantage, we put an insights-driven operating system at the core of our design, go-to-market, and digital experience solutions. Material clients make smarter growth choices because they can see clearly how and when to take the shots that count. Together, we connect consumer intelligence with customer demand generation to build lasting, profitable relationships. About the Senior Architect / AI Context Engineer Role The Senior Architect / AI Context Engineer is a strategic generalist who operates at the intersection of enterprise architecture, AI operationalization, and context engineering. This role is responsible for authoring governance artifacts, designing agent and tool-server architectures, building reusable accelerator patterns, curating agent skills and prompt harnesses, and driving the AI-native design agenda across the organization. This is the role that bridges the gap between strategic architecture decisions and hands-on AI implementation. What You'll Do Design, author, and maintain MCP (Model Context Protocol) server architectures across recurring patterns: knowledge and memory servers, platform API bridge servers, and event- or webhook-triggered agents, following established AI-native design principles. Build and curate reusable agent skills, system prompts, scoring rubrics, and harness configurations for a library of governed agent archetypes. Author and publish enterprise governance documentation: Architecture Decision Records (ADRs), security review checklists, tiered governance model documentation, and architecture review templates for the enterprise technology intake and approval pipeline. Design and implement an enterprise context engineering layer: repo-level context file standards (AGENTS.md / CLAUDE.md conventions), templates, and harness engineering patterns. Drive execution of a governed internal agent platform pilot: author agent archetypes, configure governed sessions with scoped tool access, and validate end-to-end audit trail flows on a managed agent runtime. Develop and maintain an accelerator solution map: reusable toolkit pattern definitions, capability gap analysis, and accelerator specifications spanning all service lines. Support Enterprise Knowledge Graph scoping: ontology design, data catalog foundation architecture, and schema governance, in collaboration with data science and commercial strategy teams. Author SDLC Standards and Engineering Operating Model artifacts: quality gates, PR/review standards, Definition of Done/Ready templates, CI/CD control specifications. Produce EA leadership artifacts: Enterprise Capability Maturity Map, Technology Demand and Decision Flow Dashboard, Application/Tool Portfolio Map, cross-lane integration maps, and an AI Readiness Scorecard. Operate as the primary technical liaison between the enterprise architecture function and service line teams, translating strategic architecture intent into actionable engineering guidance. About You 8+ years in software architecture, solutions architecture, or enterprise architecture roles. Demonstrated experience designing and building AI/LLM-integrated systems: agent architectures, prompt engineering, RAG pipelines, tool-use patterns. Strong understanding of context engineering: structured prompt design, system prompt authoring, knowledge retrieval optimization, context window management. Experience with at least two of: MCP (Model Context Protocol), LangChain/LangGraph, Claude API, OpenAI API, or equivalent LLM orchestration frameworks. Proficiency in multiple programming languages (Python, TypeScript/Node.js required; others a plus). Proven track record authoring governance artifacts: ADRs, architecture standards, SDLC documentation, security review frameworks. Experience with enterprise platform ecosystems: Atlassian (Confluence, Jira), Azure, GitHub, Salesforce. Strong technical writing and documentation skills; able to produce executive-ready architecture briefs and technical specifications simultaneously. Preferred Qualifications Hands-on experience with a major agentic AI ecosystem: model providers' agent runtimes, skill and tool definitions, MCP servers, and managed or hosted agent platforms. Background in market research, consulting, or insights/analytics industries. Experience with knowledge graph design, ontology modeling, or semantic data architectures. Familiarity with institutional memory and knowledge management platforms, particularly internal developer tooling that exposes organizational context to AI agents. A grounded perspective on AI adoption: recognizing that velocity bottlenecks in AI-enabled delivery are typically process habits and organizational culture rather than tooling capability. Experience with enterprise governance models (TOGAF, Zachman, or custom tiered governance). Why Work for Material? Material is a global company and we work with leading brands worldwide. We create and launch new brands and products, putting innovation and value creation at the center of our practice. Our clients are leaders in their class, across sectors from technology to retail, transportation, finance, and healthcare. Material employees join a peer group of exceptionally talented colleagues across the company, the country, and the world. We develop capabilities and leading-edge market offerings across seven global practices including strategy and insights, design, data & analytics, technology, and tracking. A community focused on learning and making an impact. Material is an outcomes-focused company. We create experiences that matter, create new value, and make a difference in our clients’ lives and their customers’ lives. Pay Range: $150,000.00 – 180,000.00 The range shown represents a grouping of relevant ranges currently in use at Material. Actual range for this position may differ, depending on location and specific skillset required for the work itself. Equal Employment Opportunity All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law. Privacy Statement Material is committed to protecting privacy in our recruiting processes for all candidates. For more information, please refer to our Privacy Policy. If you need support with a privacy-related matter, please send an email to: [email protected] We respect the privacy of candidates for employment. This Privacy Policy sets forth how we will use the information we obtain when you apply for a position through this career site. By engaging with us in the candidacy process, you are deemed to have consented to these terms. If you do not consent to the terms of this Privacy Policy, please do not submit information to us. Material drives intelligent growth for ambitious businesses and leading brands. Customer understanding is more potent and drives greater value when insights go to work directly within marketing and experience priorities. To give our clients that advantage, we put an insights-driven operating system at the core of our design, go-to-market and digital experience solutions. Our clients make smarter growth choices because they can see clearly how and when to take the shots that count. Together, we connect consumer intelligence with customer demand generation to build lasting, profitable relationships.

Senior Architect / AI Context Engineer.

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