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

Description

Engineers often speak of building impactful systems. Here, you will demonstrate it: continuous deployment, rigorous assessment, and operational AI systems that directly influence U.S. government technology. No résumé posturing. No abstract theory. Only production work delivered weekly, in demanding conditions.

Gauntlet for America is a fully funded, competitive 10-week fellowship created to develop AI-native engineering capacity for United States federal agencies. It serves as an intensive proving environment for experienced engineers prepared to show they can design and deploy production-grade AI systems where reliability, security, and tangible impact are non-negotiable.

Participants deliver work weekly, function under rigorous evaluation, and collaborate with other elite engineers. Successful 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 intense workload (80–100 hours/week) structured to accelerate learning velocity, performance signal, and professional trajectory.

Program Outcomes:

  • 10+ production-grade AI systems delivered throughout the fellowship
  • Guaranteed placement in a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribute to high-impact infrastructure defining how the U.S. government develops and runs technology
  • Enter a community of AI-native engineers working at the cutting edge of public sector technology

If you are prepared to be assessed on output — not academic background — submit your application today.

What you will be doing

  • Deliver production-ready AI systems weekly under firm deadlines
  • Develop using contemporary AI-native methods (agents, tool integration, evaluations, retrieval, deployment pipelines)
  • Operate and compete with elite engineering peers in a feedback-intensive setting
  • Engage with authentic, ambiguous challenges reflective of government and enterprise contexts
  • Convert real requirements into scoped, dependable, shippable systems

What you will NOT be doing

  • Attending theoretical lectures or passive instruction — all time is dedicated to building and deploying
  • Delaying deployment for months — you will release operational systems each week
  • Depending on academic pedigree, credentials, or interview charisma for placement — your shipped work is the sole evaluation criterion
  • Operating in a consequence-free environment — the systems you create function under authentic security and reliability demands

Key responsibilities

Deliver production-quality AI systems under operational constraints that validate readiness for federal engineering responsibilities.

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...

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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
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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.
STEP 4

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proctored test.

Accept job offer.
STEP 6

Accept job offer.

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What you will learn

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

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

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

  • Agent architectures, evaluations, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-level execution: QA, reliability, and rigorous operational standards
  • Fine-tuning + deployment strategies (LoRA/QLoRA + production integration)
  • Multi-agent modernization applied to real-world legacy codebases
  • Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)

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Premium pay for premium talent

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