Jobs / United States / Juul Labs INC
Enterprise AI Systems Engineer
Juul Labs INC · 🇺🇸 Austin, Texas, United States; Dallas, Texas, United States; San Francisco, California, United States; Washington, District of Columbia, 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 7 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Apr 2026) — the step every H-1B hire needs first. USCIS also records 6 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 Juul Labs INC paid sponsored hires in similar roles1 certified filing for “Software Engineer, Tools & Test” (Software Quality Assurance Analysts and Testers) in CA: $155k–$155k, median $155k. Most were filed at wage level I (100%) — 1 lottery entry, ≈15% 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 — Juul Labs INC
The US Department of Labor certified 7 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Apr 2026) — the step every H-1B hire needs first. USCIS also records 6 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 Juul Labs INC →
About the role
THE COMPANY: Juul Labs's mission is to transition the world’s billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world’s most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent. We are a diverse team that is united by this common purpose and we are hiring the world’s best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details. ROLE AND RESPONSIBILITIES: • You own these platforms end to end. What you build gets used across the whole company, and you decide how AI runs here rather than inheriting someone else's design. • Administer our enterprise Claude, Gemini, OpenRouter, Cursor and NotebookLM tenants. User provisioning, groups and roles, workspace configuration, and tenant security settings. • Build and maintain the content that makes those platforms useful: skills, prompts, projects, connectors, and the documentation behind them. Drive adoption across 250 users and growing. • Track consumption and spend across all three platforms. Report on usage, find idle seats, and support the business-unit chargeback model. • Keep the platforms running. Availability monitoring, feature rollouts, user issue triage, and escalation ownership when something breaks. • Build and operate the MCP servers and gateways that connect these platforms to internal systems, with least-privilege access and full audit logging. • Run the LLM gateway that centralizes routing, authentication, rate limiting, logging, and policy enforcement across model providers. • Choose the right model for each workload, commercial or open-weight, based on cost, latency, capability, and how sensitive the data is. • Build agentic workflows and automations against internal APIs and tools, with the evaluation and guardrails to keep them predictable. • Architect and run AI workloads on AWS and GCP: compute, networking, IAM, secrets management, private connectivity, Bedrock, and Vertex AI. • Own the code in GitHub and write most of it yourself, mostly Python and TypeScript. Branch protection, access control, secret scanning, and Actions pipelines. • Instrument the stack for cost, performance, and security telemetry, and build the reporting that leadership and finance rely on. • Enforce data handling, retention, and access policy alongside Cybersecurity and AI Governance, and write the runbooks and standards behind it. • Perform related duties as assigned, within your scope of practice PERSONAL AND PROFESSIONAL QUALIFICATIONS: • 5+ years in software, cloud, or platform engineering, including recent hands-on work building and running LLM-based systems. • Experience administering an enterprise SaaS or AI tenant at scale: access management, configuration, cost control, and adoption. • Working knowledge of both commercial and open-weight LLMs, including prompt engineering, evaluation, retrieval, and agentic patterns. • Hands-on with Model Context Protocol (MCP), MCP gateways, or LLM gateways. Comparable API integration and middleware experience counts. • AWS and GCP architecture, including IAM, networking, secrets management, and managed AI services. • GitHub and standard engineering discipline: version control, code review, testing, CI/CD, and infrastructure as code. • Strong Python and/or JavaScript/TypeScript for building integrations, automations, and internal tooling. • Security and data governance fundamentals applied to AI work: least