Gauntlet Fellow - Gauntlet AI
Gauntlet is a fully funded, selective 10-week fellowship for experienced engineers who want to accelerate their careers by proving they can build and ship production-grade AI systems under real-world pressure. Fellows ship weekly, work alongside experienced operators, and get direct exposure to founders, CTOs, and hiring partners. In our most recent cohort, challengers secured 300+ first-round interviews with hiring partners. Our goal is for 100% of program graduates to receive offers from our partner network, with a minimum starting compensation of $200,000. The program runs 10 weeks: 3 weeks remote, followed by 7 weeks onsite in Austin, Texas. Fellows should expect a high-intensity schedule (80–100 hours/week) designed to maximize learning speed, signal, and career outcomes. Outcomes: 10+ deployed AI applications shipped during the fellowship Access to Gauntlet’s alumni + hiring partner network Graduates receive $200,000+ job offers from hiring partners If you build fast, ship under pressure, and want your output — not your resume — to determine your next role, apply now. Ship production-ready AI applications every week on strict deadlines Build with modern AI-first workflows (agents, tool use, evals, retrieval, deployment) Collaborate and compete alongside top engineering talent in a high-feedback environment Present work directly to CTOs, founders, and hiring partners Translate real briefs into scoped, reliable, deployable systems Develop and ship production-grade AI systems weekly, converting proven engineering performance into $200K+ career outcomes through Gauntlet's hiring partner network. 3+ years of professional engineering experience (or equivalent ability) Have independently designed, implemented, and deployed at least one working software system to production or active usersHigh responsiveness to feedback and extreme execution intensity Authorized to work in the U.S. without visa sponsorship Willing to commit to 80–100 hour weeks and relocate to Austin for 7 weeks
- Software Development
Наблюдалась 2026-09-14, впервые 2026-09-14, источник — Crossover.