Jobs / United States / shifttechnology
QA Engineer Intern (6 months)
shifttechnology · 🇺🇸 Location unlisted
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
- 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.
- 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).
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Sponsor Radar — shifttechnology
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About the role
Shift delivers AI agents that transform insurers' most critical work. By combining deep industry expertise and unmatched data resources, Shift provides proven results that have earned the trust of hundreds of the world's leading insurers. Our insurance-grade AI is accurate, explainable, and secure—empowering human experts to move with unmatched speed, total confidence, and a renewed focus on the people they serve. Your browser does not support the video tag. Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance. Learn more at www.shift-technology.com Shift Technology : Shift is the leading AI platform for insurance. Shift combines generative, agentic, and predictive AI to detect fraud, assess risk, and recommend actions throughout the claims process. Our teams tackle complex data challenges and bring advanced models into production at scale, giving insurers deeper insights into their data while helping their customers get paid faster and enjoy a smoother claims experience. Our technology is adopted and trusted by the world’s leading insurers. The QA Engineering Team 🧪: The Quality Assurance team, part of Engineering, makes sure that Shift can ship fast and safely. Our AI-driven software is deployed for insurers worldwide, across many multi-tenant environments, and we use Generative AI, LLM agents, and modern automation to solve quality challenges at this scale. Here are just a few of the areas we work on: • Release validation: risk-based testing and delivery automation; • Automated regression suites and test automation; • Functional test coverage and test gap analysis; • Test data generation and test environment provisioning; • AI-powered QA tooling, built with LLMs and agents, that engineers and QA leads use every day Working with Engineering teams and QA leads, we replace manual QA effort with intelligent tooling, and we measure the time it saves. Your key responsibilities🧑💻: You’ll own an end-to-end project that moves a real QA bottleneck from manual effort to intelligent tooling. You will build something the QA engineering teams use in their day-to-day work, not a proof of concept that stays on a shelf. Your subject will be defined with you during the selection process, within one of these example missions: • AI-driven release validation: build a “release copilot” that analyzes release tickets and code changes to compute risk scores and generate risk-based test plans. It also helps run bug bash sessions (scope, assignment, triage, duplicate detection) and drafts test reports and release notes. • Functional coverage and test gap analysis: use code intelligence and LLMs to detect shipped features, feature flags, and endpoints, map them against environment configurations and automated regression suites, and show untested areas in a live coverage dashboard. • Synthetic test data and environment provisioning: design a data generation and seeding pipeline (CLI / API) that produces realistic, deterministic, and privacy-compliant datasets, so teams can provision and reset test environments on demand, integrated into CI/CD. Along the way, you’ll learn how QA, Engineering, and Product work together to ship AI software to insurers around the world. Your project will go beyond a prototype: you will validate it on real releases, hand it over with documentation, and present the results to leadership. • Your profile and requirements✅: • You are currently in your final year (BAC+5, Master 2 or engineering school) in Computer Science, Software Engineering, Data, or AI. • You have solid programming skills in Python , TypeScript/JavaScript , or C#