Gen AI Front End Engineer

GenAI Front-End Engineer (Embedded AI & SDK)
Location: South San Francisco, CA (Hybrid: 1–2 days/week on-site preferred; or remote with 4–6 hours daily PT overlap)
Contract Duration: 6 Months (Potential for extension or conversion)
Compensation: $42.15 – $90.23/hour (W2)
Benefits: Weekly direct deposit, Medical, Dental, and Vision coverage
 
Role Overview
We are seeking a GenAI Front-End Engineer to architect and build a reusable, embeddable conversational and analytics UI layer. In this role, you will develop SDKs and micro-frontends designed to integrate seamlessly across multiple host applications.
You will be responsible for handling bidirectional communication with host products—ingesting authentication tokens, active screen context, and user filters—while rendering streaming responses, rich data visualizations (tables, charts), citations, and conversation threads.
 
Key Responsibilities

• Architect embeddable UI solutions using Micro-Frontends, Web Components, Module Federation, or secure iframes.
• Design robust integration contracts, SDK surfaces, lifecycle hooks, and event-driven communication protocols for consuming host applications.
• Implement real-time, multi-turn Generative AI interfaces featuring token streaming, structured outputs (tables, charts, inline citations), and interactive clarification flows.
• Capture and manage host context dynamically (active routes, global filters, selected entities, user state).
• Manage authentication handshakes, secure token lifecycles, and resilient streaming API connections.

 
Qualifications & Core Requirements
Must-Have

• Technical Mastery: Production-grade expertise in React, TypeScript, and Modern JavaScript.
• Embedding & Integration: Proven experience embedding UI services, micro-frontends, or client-side SDKs inside third-party or multi-team host applications.
• API & Contract Design: Strong background defining clean SDK interfaces, versioned APIs, event buses, and callback mechanisms.
• GenAI UI Systems: Hands-on experience developing streaming LLM interfaces, handling multi-turn conversations, state hydration, and UI recovery/error states.
• Data Visualization: Experience rendering complex, structured responses, including charts, dynamic tables, and reference citations.
• Networking & Security: Deep understanding of REST/SSE/WebSocket streaming protocols, auth handshakes, and token lifecycle management.

 
Nice-to-Have

• Experience building and publishing reusable UI SDKs/packages distributed across multiple cross-functional engineering teams.
• Familiarity with MCP (Model Context Protocol) clients, embedded analytics, or enterprise copilot frameworks.
• Experience with AWS cloud ecosystems, Amazon Bedrock, and agentic backend architectures (e.g., AgentCore).

#TMRD