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

Most engineers discuss the importance of meaningful work. Here, you will prove that commitment: continuous delivery, rigorous assessment, and operational AI systems that directly influence U.S. government technology. No performative credentialing. No abstract theory. Only production results every week, delivered under real constraints.

Gauntlet for America is a fully funded, competitive 10-week fellowship built to develop AI-native engineering talent for United States federal agencies. It operates as a high-pressure validation environment for accomplished engineers seeking to demonstrate mastery in building and deploying production-quality AI systems where reliability, security, and tangible outcomes are non-negotiable.

Fellows deliver weekly, undergo continuous evaluation, and work alongside 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 directly affect government operations.

The fellowship spans 10 weeks: 3 weeks conducted remotely, then 7 weeks on-site in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours/week) structured to accelerate skill acquisition, performance signal clarity, and professional advancement.

Program Outcomes:

  • 10+ production-ready AI systems delivered throughout the fellowship
  • Guaranteed placement in a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribution to high-impact systems influencing how the U.S. government develops and deploys technology
  • Access to a network of AI-native engineers working at the forefront of public sector technology transformation

If you are prepared to be assessed by what you deliver—not your academic pedigree—apply today.

What you will be doing

  • Deliver production-ready AI systems weekly under fixed deadlines
  • Construct solutions using contemporary AI-first methodologies (agents, tool integration, evaluation frameworks, retrieval, production deployment)
  • Operate in a collaborative yet competitive setting with elite engineering peers in a feedback-rich environment
  • Engage with authentic, ambiguous challenges that mirror government and enterprise operational contexts
  • Convert real-world requirements into scoped, dependable, deployable technical solutions

What you will NOT be doing

  • Attending theoretical lectures or passive instruction—every moment is dedicated to building and deployment
  • Experiencing months-long delays before production deployment—you will release functional systems each week
  • Depending on academic credentials, institutional reputation, or interview presentation to secure your role—your delivered production work is the sole evaluation criterion
  • Operating in a consequence-free testing environment—your systems will meet actual security and reliability requirements

Key responsibilities

Deliver production-grade 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...

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 Instruction (Weeks 1–3) — Foundations in AI-First Engineering

  • Modern AI-first development approaches (coding agents, MCP, real-time collaboration tools)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector database systems
  • Fast-cycle project delivery focused on shipping under operational constraints

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

  • Agent architectures, evaluation frameworks, verification, and observability tooling (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-level delivery practices: quality assurance, system reliability, and high-standard execution
  • Fine-tuning and deployment strategies (LoRA/QLoRA + production integration patterns)
  • Multi-agent modernization approaches for existing production codebases
  • Multimodal AI development (image/video/voice) and scalable cloud infrastructure (AWS/Azure)

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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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