Hiring For "AI Architect" Remote

Hi,

Role: Senior AI Experience Platform Architect

Location: Remote

Duration: FTE

Candidates must be located within 100 miles from these locations: Bloomington, IL; Richardson, TX; Atlanta, GA; Pheonix, AZ

Must have:

• Hands-on development of agentic AI agents and reusable AI skills.
• Experience building tools using Claude Code, Claude Cowork, Claude Design, ChatGPT Work, and/or Codex, as applicable to demonstrated hands-on experience.
• Strong experience structuring information for AI use, including information architecture, taxonomy, or schema design.
• MCP (Model Context Protocol) experience.
• Production coding experience with Python and TypeScript.
• CI/CD and pipeline automation, such as GitHub Actions, GitLab CI, or equivalent.
• Experience with instrumentation, telemetry, observability, or event tracking.
• Ability to integrate AI tools with live design files, research data, code, and workflow systems.

Position Overview:

Build the technical foundation for reusable AI capabilities that can connect to trusted knowledge, live enterprise systems, and multi-step workflows. This role focuses on creating production-ready agentic AI applications and integrations while establishing the architecture, knowledge structures, automation, observability, and governance needed to support consistent adoption across teams and departments.

The position works closely with an AI Design Engineer and partners across design, engineering, and business stakeholders to define practical solutions, evaluate trade-offs, and implement scalable approaches.

Responsibilities:

• Define and implement clean boundaries between reusable AI tools and the knowledge sources they consume.
• Structure and curate trusted knowledge across user research, brand and design-system guidance, front-end components, accessibility requirements, and UX-writing standards.
• Develop taxonomy, schema, chunking, metadata, and content-lifecycle practices to support reliable AI and human retrieval.
• Create shared, machine-readable sources of design and accessibility rules that can be applied consistently across multiple tools.
• Implement persistent identifiers, citations, and provenance to trace generated design or code artifacts to their originating sources and workflow steps.
• Design and build agent connections to live design files, research repositories, codebases, and enterprise systems using MCP or comparable integration patterns.
• Automate handoffs into systems such as GitHub and Jira, including engineering-review workflows and integration with knowledge-management platforms.
• Instrument the toolchain to provide visibility into cycle time, quality scores, human-review rounds, exceptions, adoption, and research traceability.
• Build mechanisms for quality checks, false-positive tuning, overrides, audit trails, and release gates.
• Partner closely with the AI Design Engineer on the design-facing meaning and acceptance thresholds for quality checks.
• Map target architecture, dependencies, service boundaries, knowledge locations, and the skill registry.
• Present viable technical options and trade-offs and gain stakeholder agreement before implementation.
• Write production code and establish automated build and release pipelines.
• Create playbooks that support the operating model through changes in tools or models.

Requirements:

• Recent hands-on experience building an agentic AI application, reusable agent capability, or multi-step workflow used by a team, beyond experimentation with prompts or chat interfaces.
• Strong production software-engineering skills in Python and TypeScript, including APIs, integrations, testing, maintainability, and secure handling of enterprise data.
• Experience structuring unstructured information for reliable AI and human retrieval using taxonomy, schema design, metadata, persistent identifiers, and content-lifecycle practices.
• Hands-on experience with RAG or comparable grounding patterns, including retrieval quality, citations, source freshness, and failure handling.
• Experience with MCP or equivalent tool and data-source integration patterns for connecting AI agents to repositories, applications, and live knowledge.
• CI/CD and workflow-automation experience using GitHub Actions, GitLab CI, or equivalent tooling.
• Instrumentation and observability experience, including events, logs, metrics, audit trails, and dashboards that explain automated workflow activity.
• Ability to create clear architecture and process diagrams and facilitate decisions across design, engineering, and business stakeholders.
• Ability to present options and trade-offs, recommend a path, keep stakeholders informed, and execute independently without detailed daily direction.
• Strong peer-collaboration skills and the ability to work as a tightly coupled partner with the AI Design Engineer while sharing decisions without territorial ownership.

Preferred Qualifications:

• Experience with AI coding or agent environments such as Claude Code, Codex, ChatGPT Work, or comparable platforms.
• Familiarity with the structure of Figma files, design tokens, component libraries, or Figma plugin code.
• Experience with design linting, static analysis, policy-as-code, or rules engines.
• Working knowledge of Jira, Confluence, GitHub, and enterprise knowledge-management platforms and their data models or APIs.
• Microsoft Copilot Studio or comparable low-code automation experience.
• Experience in insurance, financial services, healthcare, or another highly regulated environment.
• Experience taking an AI or knowledge platform from prototype to team or enterprise adoption.

In compliance with the salary transparency law, the expected salary range for this role is $140k -150k/Annum. Actual compensation depends on experience and interview evaluation

Best Regards,

Kripali Sahu

Technical Recruiter | Empower Professionals

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