Jobs / United States / Faraday & Future INC
Senior AI & Business Operations Engineer
Faraday & Future INC · 🇺🇸 El Segundo, California, United States
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 12 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 7 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Faraday & Future INC paid sponsored hires in similar roles1 certified filing for “Manager, Aftersales Business Operations – EAI Robotics” (General and Operations Managers) in CA: $169k–$169k, median $169k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Faraday & Future INC
The US Department of Labor certified 12 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 7 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Faraday & Future INC →
About the role
The Company: Faraday Future (FF) is a California-based mobility company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility. We’re producing user-centric, technology-first vehicles to establish new paradigms in human-vehicle interaction. We’re not just seeking to change how our cars work – we’re seeking to change the way we drive. At FF, we’re creating something new, something connected, and something with a true global impact. Your Role: As Senior AI & Business Operations Engineer , you will be responsible for building an enterprise-grade AI Agent platform that elevates large model capabilities from an “information generation tool” to “executable business productivity,” driving AI to play a deep role in the company’s core business processes and operational decision-making. You will lead the design and implementation of an enterprise-level Agent system similar to OpenClaw, connecting AI models, enterprise data, and business systems to deliver an end-to-end closed loop: task understanding → data retrieval → decision generation → automated execution. The platform will serve sales and commercial systems and gradually expand to enterprise operations and management scenarios. Responsibilities: • AI Agent Platform Development : Design and implement an enterprise-grade AI Agent platform (Agent Runtime) supporting task understanding, planning, multi-step execution, and state management (memory). Build a unified Tools Layer that encapsulates enterprise APIs, data services, and operational capabilities, enabling Agents to securely invoke CRM, ERP, data platforms, and other systems. Design multi-Agent and multi-step collaboration mechanisms to support automated execution of complex business workflows. • Workflow Automation & Orchestration : Based on OpenClaw or similar frameworks, build cross-system task orchestration capabilities to achieve a closed loop from AI-driven insights to business execution. Design secure and controllable execution mechanisms including approval nodes, human-in-the-loop collaboration, and rollback strategies. Drive AI automation in business processes such as customer follow-up, task generation, data updates, and process triggering. • AI Enablement for Sales & Commercial Systems : Build AI Copilot and Agent capabilities to support sales operations, lead management, and customer engagement. Integrate with CRM, CPQ, order management, and customer service systems to achieve deep fusion of AI and business processes. • AI Enablement for Enterprise Strategy & Operations: Collaborate with management and operational teams to identify AI application scenarios in revenue growth, conversion optimization, customer operations, cost control, and risk management. Build a Decision Copilot for leadership to support data-driven decision-making. Connect data platforms and AI systems to enable the flow: Data → Insights → Decisions → Execution (via Agent automation). Establish a quantitative evaluation system linking AI outcomes to business KPIs such as revenue, conversion rates, and efficiency gains. • RAG & Enterprise Knowledge System: Build an enterprise-grade Retrieval-Augmented Generation (RAG) system integrating knowledge bases, business data, and real-time information. Support permission-aware retrieval, citation tracing, result explanation, and temporal sensitivity controls. Optimize embeddings, indexing strategies, reranking, and caching mechanisms to improve accuracy and performance. • Security, Governance & Production Systems: Design security and governance mechanisms for AI systems, including execution tiering (read-only / low-risk / high-risk operations). Build a comprehensive audit and compliance framework to make AI behavior traceable and explainable. Esta