Jobs / United States / Zscaler INC
Staff Software Development Engineer - AI Engineer
Zscaler INC · 🇺🇸 Mohali, IND
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 129 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 36 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 Zscaler INC paid sponsored hires in similar roles63 certified filings for “Sr. Staff Software Development Engineer” (Software Developers) in CA: $175k–$224k, median $200k. Most were filed at wage level IV (86%) — 4 lottery entries, ≈61% 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 — Zscaler INC
The US Department of Labor certified 129 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 36 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 Zscaler INC →
About the role
Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for an AI Engineer to join our team. This is a Hybrid role, reporting to the Engineering Manager in the Product Operations department. We are seeking a hands-on AI Engineer to help scale the agentic layer of our AI Native - Product Operations Platform. In this role, you will design and build production-grade AI systems, reusable platform capabilities, and the engineering harnesses required to safely develop, evaluate, debug, and operate AI workflows at scale. As a pragmatic builder who understands modern AI systems in practice, you will translate ambiguous business needs into scalable technical solutions in a high-velocity environment. What you’ll do (Role Expectations) • Build and scale the agentic layer of the AI Native - Product Operations Platform by designing production-grade AI systems, reusable platform capabilities, and reliable execution patterns • Develop Agentic AI capabilities by applying practical knowledge of RAG architectures, embeddings, vector retrieval, agent orchestration, and workflow state management • Design and implement AI engineering harnesses for prompt testing, agent debugging, workflow replay, evaluation, regression testing, tracing, and controlled experimentation • Build and maintain graph-based agent workflows, including multi-step reasoning flows, tool-calling paths, branching logic, human-in-the-loop checkpoints, and stateful execution patterns • Implement standards, patterns, and guardrails to ensure AI development on the platform remains scalable, reliable, observable, and cohesive Who You Are (Success Profile) • You are a pragmatic builder with a passion for rolling up your sleeves to create, iterate, and ship production-grade software. • You thrive in ambiguity and fast-paced environments, maintaining focus and execution velocity amidst rapid change. • You act like an owner, bringing deep accountability, a strong bias for action, and end-to-end execution to every project. • You are a high-trust collaborator who excels at partnering with cross-functional teams to translate business needs into technical solutions. • You champion simplicity, with a proven ability to distill complex technical problems and AI architectures into clean, actionable plans. What We’re Looking for (Minimum Qualifications) • 5+ years of industry experience with at least 2-3 years focused on building or working with AI development harnesses, including test harnesses, evaluation pipelines, workflow replay tools, tracing, observability, and prompt or agent regression testing • Proven experience building and deploying agentic AI systems, RAG architectures, embeddings, and vector retrieval systems in production environments • Familiarity with prom