Jobs / United States / Servicenow INC
Staff Software Engineer - Federal
Servicenow INC · 🇺🇸 Santa Clara, CALIFORNIA, US
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 547 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 185 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 Servicenow INC paid sponsored hires in similar roles162 certified filings for “Senior Software Engineer” (Software Developers) in CA: $144k–$204k, median $175k. Most were filed at wage level IV (45%) — 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 — Servicenow INC
The US Department of Labor certified 547 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 185 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 Servicenow INC →
About the role
Position Location: This is a Flexible (Hybrid) position based in Santa Clara, CA. Flexible positions require 2 days per week in our Santa Clara office location. Please Note: This position will include supporting our US Regulated Markets. “This position requires passing a ServiceNow background screening, USFedPASS (US Federal Personnel Authorization Screening Standards). This includes a credit check, criminal/misdemeanor check and taking a drug test. Any employment is contingent upon passing the screening. Due to Federal requirements, only US citizens, US naturalized citizens or US Permanent Residents, holding a green card, will be considered. As a Staff Software Engineer, you will independently lead the design, development, and delivery of complex, high-impact AI-native and cloud-native systems. The IC4 engineer takes ownership of critical components or features, sets technical direction within their domain, and serves as a technical resource to peers and junior engineers. They combine deep software engineering fundamentals with hands-on expertise in AI/ML integration, cloud architecture, and production systems. This role requires the ability to balance technical depth with organizational impact, working across teams to solve ambiguous problems and drive platform improvements. What you get to do in this role: Responsibility Area: Technical Leadership & Architecture • Lead the design and architecture of complex, production-critical AI-native systems, including LLM integrations, agentic workflows, retrieval pipelines, and inference services • Own end-to-end delivery of medium-to-large features or systems, including specification, design, implementation, testing, deployment, and production monitoring • Make informed architectural and technical trade-off decisions between latency, cost, scalability, reliability, and model quality • Establish evaluation frameworks, testing strategies, and production monitoring for AI-driven features; drive adoption of eval-driven development practices • Design and optimize high-performance data pipelines, embedding systems, and vector stores handling millions of rows and complex retrieval scenarios • Champion security best practices, including prompt-injection defense, data privacy, PII handling, responsible AI guardrails, and compliance with regulatory requirements • Participate in architectural reviews across teams and contribute to platform-level technical decisions • Stay current with emerging AI/ML frameworks, services, and techniques; evaluate and recommend adoption where applicable Responsibility Area: Mentorship & Technical Influence • Mentor junior and mid-level engineers (IC2/IC3) through pair programming, design reviews, architecture discussions, and hands-on coaching • Conduct thorough code reviews, including evaluation of prompts, agent logic, retrieval strategies, and AI/model behavior validation • Identify technical debt and improvement opportunities; advocate for and lead initiatives to address them • Share knowledge through documentation, brown-bag sessions, and architectural guidance • Contribute to hiring and interview processes; provide technical assessment and feedback on engineering candidates • Model best practices in software craftsmanship, testing discipline, and debugging methodology • Support onboarding of new team members and ensure knowledge transfer across projects Responsibility Area: Cross-Functional Collaboration & Communication • Work closely with product management, domain specialists, and other engineering teams to define requirements and technical specifications • Translate complex technical concepts and AI trade-offs for non-technical stakeholders (product, leadership, customers) •