Applied AI Engineer
$160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

3 weeks remote, 7 weeks onsite in Austin, TX
80–100 hours/week for 10 weeks
In-person
Short-term contract
full-time (90 hrs/week)

Applied AI Engineer   $160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

Description

Gauntlet for America is a selective, fully funded 10-week fellowship focused on developing AI-native engineering talent for the United States government.

This is an intensive proving ground for skilled engineers ready to show they can design and deploy production-grade AI systems in settings where security, reliability, and tangible impact are critical.

Participants deliver work weekly, undergo continuous evaluation, and collaborate with other top-tier engineers. Those who complete the program successfully transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that shape government operations.

The fellowship structure: 10 weeks total—3 weeks conducted remotely, then 7 weeks onsite in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours/week) engineered to accelerate learning, assessment, and professional advancement.

What to Expect:

  • Deliver 10+ production-ready AI systems over the course of the fellowship
  • Secure direct placement into a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribute to high-impact systems that influence how the U.S. government builds and deploys technology
  • Become part of a network of AI-native engineers leading innovation in the public sector

What you will be doing

  • Deliver production-ready AI applications weekly under firm deadlines
  • Develop using modern AI-first methodologies (agents, tool integration, evaluations, retrieval, deployment)
  • Engage and compete with elite engineering peers in a high-feedback setting
  • Navigate real, ambiguous problem domains reflective of government and enterprise contexts
  • Convert real-world briefs into scoped, reliable, and deployable systems

Candidate requirements

  • U.S. citizenship mandatory (no exceptions; background check will be conducted)
  • Proven engineering capability (both new graduates and seasoned engineers are eligible)
  • Prepared to relocate to Austin, TX for 7 weeks (full-time, onsite)
  • Prepared to relocate to the Washington, DC area following program completion (remote work not available)
  • Solid problem-solving skills, rapid learning capability, and sound reasoning under pressure
  • High receptiveness to feedback and capacity to perform in high-intensity settings

Meet a successful candidate

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Fabiano Lucchese
Fabiano  |  SVP of Software Engineering
Brazil

Does your company encourage your natural creativity? This Brazilian engineering leader rediscovered his purpose after unleashing both his an...

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STEP 1

Chat-style
screening interview.

Cognitive 
aptitude test.
STEP 2

Cognitive 
aptitude test.

Prove real-world 
job skills.
STEP 3

Prove real-world 
job skills.

Interview with the hiring manager.
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Accept job offer.
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Accept job offer.

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About Crossover

What you will learn

Phase 1: Remote (Weeks 1–3) — Foundations in AI-First Engineering

  • AI-first development practices (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector database systems
  • Fast-paced project sprints emphasizing delivery under constraints

Phase 2: Onsite in Austin (Weeks 4–10) — Production-Scale AI Engineering

  • Agent architectures, evaluations, verification, and observability tools (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-standard delivery: quality assurance, reliability, and rigorous execution
  • Fine-tuning and deployment methodologies (LoRA/QLoRA + production integration)
  • Multi-agent strategies for modernizing real-world codebases
  • Multimodal AI applications (image/video/voice) and scalable cloud infrastructure (AWS/Azure)

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The Olympics of work

It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.

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Premium pay for premium talent

Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.

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