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

Engineers often discuss creating meaningful systems. Here's your opportunity to demonstrate it through disciplined execution: continuous delivery, rigorous assessment, and operational AI infrastructure that directly influences U.S. government operations. No reliance on academic pedigree. No abstract assignments. Only tangible production results each week, delivered under demanding conditions.

Gauntlet for America is a fully funded, competitive 10-week fellowship built to develop AI-native engineering talent for United States government operations. It serves as a high-rigor testing environment for seasoned engineers seeking to prove their capacity to construct and maintain production-quality AI systems in contexts where dependability, security, and measurable impact are essential.

Participants deploy weekly deliverables, work within stringent evaluation frameworks, and collaborate with other accomplished engineers. Those who successfully complete the program transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that directly affect government operational capability.

The fellowship spans 10 weeks: an initial 3-week remote phase, then 7 weeks in-person in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours weekly) structured to accelerate skill acquisition, performance visibility, and professional advancement.

Program Outcomes:

  • Delivery of 10+ production-grade AI systems throughout the fellowship period
  • Guaranteed placement into federal engineering positions (GS-12 level, ~$160K–$200K+ based on background + full benefits)
  • Contributions to high-impact infrastructure shaping U.S. government technology development and operations
  • Access to a professional network of AI-native engineers working at the leading edge of public sector technology

If you're prepared to be assessed on delivered work—not academic credentials—submit your application now.

What you will be doing

  • Deliver production-quality AI applications weekly within fixed timelines
  • Develop systems using contemporary AI-native methodologies (agents, tool integration, evaluation frameworks, retrieval architectures, deployment pipelines)
  • Operate in a collaborative, competitive setting with top-tier engineering peers and continuous feedback
  • Engage with authentic, unstructured problem domains resembling government and enterprise operational environments
  • Convert real-world requirements into well-defined, dependable, production-ready systems

What you will NOT be doing

  • Participating in theoretical lectures or passive instruction—every session is dedicated to active development and deployment
  • Experiencing months-long delays before production deployment—your systems go live each week
  • Depending on academic background, institutional reputation, or interview skills for placement—only your shipped work determines advancement
  • Operating in a simulated, low-risk environment—your systems must meet authentic security and reliability requirements

Key responsibilities

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

Candidate requirements

  • U.S. citizenship mandatory (no exceptions; background investigation required)
  • Proven engineering capability (both recent graduates and experienced professionals eligible)
  • Commitment to relocate to Austin, TX for 7 weeks (full-time, on-site participation)
  • Commitment to relocate to Washington, DC metropolitan area following program completion (remote work not available)
  • Exceptional analytical reasoning, rapid learning capacity, and sound judgment under pressure
  • Strong receptiveness to critique and capability to perform in high-intensity settings

Meet a successful candidate

Watch Interview
Fabiano Lucchese
Fabiano  |  SVP of Software Engineering
Brazil

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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.

Frequently asked questions

About Crossover

What you will learn

Phase 1: Remote Period (Weeks 1–3) — Foundations of AI-Native Engineering

  • AI-native development methodologies (coding agents, MCP, synchronous collaboration tools)
  • Retrieval-Augmented Generation (RAG) architectures, embeddings, and vector database implementation
  • Accelerated project cycles emphasizing constrained delivery

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

  • Agent architectures, evaluation systems, verification protocols, and observability tooling (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-standard delivery practices: quality assurance, system reliability, and rigorous execution standards
  • Fine-tuning and deployment strategies (LoRA/QLoRA + production integration workflows)
  • Multi-agent approaches to modernizing existing production codebases
  • Multimodal AI development (image/video/voice processing) 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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