Jobs / United States / Scale AI INC
Frontier Agents Engineer (Forward Deployed Engineering)
Scale AI INC · 🇺🇸 San Francisco, CA; New York, NY
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 74 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 3 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 Scale AI INC paid sponsored hires in similar roles29 certified filings for “Software Engineer” (Software Developers) in CA: $210k–$235k, median $216k. Most were filed at wage level II (34%) — 2 lottery entries, ≈31% 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 — Scale AI INC
The US Department of Labor certified 74 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 3 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 Scale AI INC →
About the role
About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media, telecommunications, and government to build production AI agents that automate complex workflows, reason over enterprise knowledge, and operate safely at scale. The Opportunity The hardest part of enterprise AI isn't building a great model—it's building AI systems that reliably operate inside complex production environments. As a Frontier Agent Engineer (Forward Deployed Engineering) , you'll work directly with strategic enterprise customers to architect, integrate, deploy, and operate production AI systems. You'll combine modern software engineering, distributed systems, cloud infrastructure, and frontier AI technologies to transform cutting-edge models into reliable enterprise software. Unlike traditional infrastructure or platform roles, you'll work at the intersection of AI and enterprise engineering. You'll design production agent architectures, integrate with customer systems, deploy AI into mission-critical workflows, and help shape the engineering best practices for the next generation of enterprise AI. If you enjoy solving difficult systems problems, rapidly prototyping new AI capabilities, and bringing frontier AI into production, you'll fit right in. What You'll Build Enterprise AI Systems • Architect and deploy production AI systems that integrate seamlessly into complex enterprise environments, including cloud platforms, data warehouses, internal APIs, business applications, and proprietary software systems. • Design scalable agent architectures that combine LLMs, retrieval, memory, tools, structured knowledge, and enterprise data into reliable production workflows. • Build robust integrations that allow AI agents to safely interact with customer systems while meeting enterprise requirements for security, governance, and compliance. • Rapidly prototype new AI capabilities and evolve successful prototypes into production-ready systems. AI Platform Engineering • Build the production infrastructure that enables frontier AI research to become reliable enterprise software. • Develop agent runtimes, orchestration frameworks, context pipelines, execution services, and tool integrations that power production AI systems. • Engineer systems for reliability, observability, latency, scalability, retries, fallback strategies, and graceful degradation. • Design human-in-the-loop workflows that effectively combine AI automation with expert oversight. • Build deployment patterns that allow AI systems to evolve safely through continuous delivery and experimentation. Production AI Quality • Operationalize modern AI quality systems that ensure production agents remain reliable as models, prompts, and customer data evolve. • Deploy evaluation harnesses using offline benchmarks, online experiments, golden datasets, regression suites, and LLM-as-a-Judge to detect quality regressions before they impact customers. • Implement tracing, observability, monitoring, guardrails, grounding, and safety mechanisms that enable production AI systems to operate with confidence. • Partner closely with Applied AI engineers to productionize new evaluation methodologies, retrieval strategies, reasoning architectures, and emerging AI capabilities. • Rapidly evaluate newly released models, agent frameworks, evaluation methodologies, and developer tooling, determining how they can be safely adopted into production systems. Customer Innovation •