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)

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

Description

Many engineers claim to build meaningful systems. Here's your opportunity to demonstrate that capacity: unrelenting delivery cycles, rigorous assessment, and live AI infrastructure directly influencing U.S. government operations. No credential performance. No abstract challenges. Only weekly production releases, executed under deadline pressure.

Gauntlet for America is a fully funded, competitive 10-week fellowship created to develop AI-native engineering talent for United States government service. It functions as a high-pressure validation environment for seasoned engineers prepared to show they can construct and maintain production-quality AI systems in contexts where dependability, security, and tangible impact are critical.

Participants deliver weekly output, work under continuous evaluation, and collaborate with other elite engineers. Upon completing the program successfully, graduates transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that directly affect government operations.

The fellowship spans 10 weeks: 3 weeks conducted remotely, then 7 weeks onsite in Austin, Texas. Participants should anticipate an intensive workload (80–100 hours/week) structured to accelerate learning velocity, performance visibility, and professional advancement.

Program Outcomes:

  • 10+ production-grade AI systems delivered throughout the fellowship
  • Direct transition into federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribution to high-stakes systems defining how the U.S. government develops and deploys technology
  • Membership in a community of AI-native engineers working at the leading edge of public sector technology

If you're prepared to be measured by your output — not your academic background — submit your application now.

What you will be doing

  • Deliver production-quality AI applications weekly against firm deadlines
  • Develop systems using contemporary AI-first methodologies (agents, tool integration, evaluations, retrieval, deployment)
  • Compete and cooperate with exceptional engineering peers in a feedback-intensive setting
  • Engage with authentic, ambiguous problem domains resembling government and enterprise scenarios
  • Convert real project briefs into scoped, dependable, production-ready systems

What you will NOT be doing

  • Attending theoretical instruction or passive training sessions — all time is dedicated to development and deployment
  • Delaying months before your code reaches production — you will release functional systems each week
  • Depending on degrees, institutional prestige, or interview results to secure your role — only your shipped work determines success
  • Operating in low-consequence practice environments — your systems function under authentic security and reliability requirements

Key responsibilities

Deliver production-ready AI systems under authentic operational constraints that verify preparedness for federal engineering positions.

Candidate requirements

  • U.S. citizenship required (no exceptions; background check required)
  • Demonstrated engineering ability (new grads and experienced engineers considered)
  • Willing to relocate to Austin, TX for 7 weeks (full-time, in person)
  • Willing to relocate to the Washington, DC area upon program completion (no remote roles)
  • Strong problem-solving ability, learning speed, and clear reasoning under pressure
  • High responsiveness to feedback and ability to operate in high-intensity environments

Meet a successful candidate

Watch Interview
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...

Meet Fabiano

Applying for a role? Here’s what to expect.

Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.

Chat-style
screening interview.
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.
STEP 4

Interview with the hiring manager.

Pass
proctored test.
STEP 5

Pass
proctored test.

Accept job offer.
STEP 6

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 methodologies (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector databases
  • Accelerated project cycles emphasizing delivery under constraints

Phase 2: Onsite in Austin (Weeks 4–10) — Scaled Production AI Systems

  • Agent architectures, evaluation frameworks, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-standard delivery: quality assurance, reliability engineering, and rigorous execution
  • Fine-tuning and deployment strategies (LoRA/QLoRA + production integration)
  • Multi-agent modernization applied to existing real-world codebases
  • Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)

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Why Crossover

Recruitment sucks. So we’re fixing it.

The Olympics of work

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.

Premium pay for premium talent

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.

Shortlist by skills, not bias

Shortlist by skills, not bias

We don’t care where you went to school, what color your hair is, or whether we can pronounce your name. Just prove you’ve got the skills.

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