AI Interface Engineer

• Work closely with product, design, and engineering to create a repeatable path from prototype to production, where agent-mediated experiences are tested against live data over MCP before they ever reach a spring review.
• Build conversational and agentic experiences directly into our product surface, giving customers natural language access to the workflows and data that underpin our real-time platform.
• Develop and maintain product-facing MCP servers and agent tooling and internal automation - safely and at scale.
• Apply these same agent-driven patterns to internal tools first - configuration interfaces, admin workflows - proving out the approach before rolling it outward to customer-facing surfaces.
• Own prompt engineering end-to-end: authoring, versioning, and systematically evaluating prompts, tool specs, and agent behaviors using reproductible test harnesses tied to measurable outcomes.
• Build out an evaluation framework for agentic UX that tracks task completion, latency, guardrail adherence, and continuous improvement loops grounded in real usage data.
• Champion agent-mediated interface patterns organization-wide, working across frontend, backend, product and platform to make this a core architectural approach rather than an afterthought.
• See initiatives through from initial discovery and prototyping all the way to production launch, instrumentation, and iterative improvement.

• Demonstrated experience shipping production applications built around LLMs and agent frameworks, including tool use, multi-turn context management, and safe handling of non-deterministic model outputs.
• Strong product and UX sensibility: ability to translate ambiguous workflows into clear interaction designs and to advocate effectively for user needs in cross-functional discussions.
• Fluency in prompt engineering, including multi-turn conversation design, tool definition, context-window management, and systematic evaluation behavior.
• Full-stack engineering ability, with a strong frontend depth in Typescript and React and the ability to move into Python backends, built REST/WebSocket services, and wire interfaces to real data sources.
• Hands-on experience with agent tool protocols (MCP or equivalent) and with designing tool surfaces that are both expressive for agents and safe at production scale.
• Experience with agent-mediated code generation tools (Claude Code, Codex) in a production setting, including writing prompts, skills, or agents that non-engineers use.
• Experience with cloud platforms (AWS preferred) and using modern CICD workflows.
• Comfort operating in ambiguity within an emerging engineering practice, partnering with other founding contributors to set direction and establish patterns across teams., * Bachelor's degree in computer science, Human-Computer Interaction, Design, or related field.
• Experience integrating with collaboration and knowledge based systems such as GitHub, Confluence, Jira, or Notion, including building programmatic access layers over them.
• Experience working directly with designers in Figma or comparable tooling, including translating design intent into working code and feeding design integration from production data.
• Background in developer tooling, internal admin platforms, or configuration-heavy products.

Bonus Experience

• Experience designing information architecture for knowledge-dense domains, unifying structured and unstructured content (code, documents, issue trackers, wikis) into coherent representations that both humans and agents can navigate.
• Experience with retrieval, semantic search, or vector-store backed knowledge systems at sclae.
• Experience building and operating microservices into production.
• Exposure to IoT device management, real-time data systems, or other data-dense domains where agent-mediated interfaces offer clear leverage.