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 work of consequence. This is an opportunity to substantiate that claim: continuous deployment, rigorous assessment, and operational AI systems that directly influence United States government functions. No performative credentialing. No abstract assignments. Only production deliverables every week, under demanding conditions.

Gauntlet for America is a fully funded, competitive 10-week fellowship built to develop AI-native engineering capacity for the U.S. government. It functions as a high-rigor proving ground for seasoned engineers seeking to validate their ability to construct and maintain production-grade AI systems in contexts where reliability, security, and tangible impact are essential.

Participants deploy weekly, face stringent evaluation, and train with other top-tier engineers. Upon successful completion, 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 a demanding schedule (80–100 hours/week) structured to maximize learning velocity, performance signal, and professional advancement.

Outcomes:

  • 10+ production-ready AI systems delivered during the fellowship
  • Direct transition into a federal engineering position (GS-12 equivalent, ~$160K–$200K+ based on experience + full benefits)
  • Contribute to high-impact systems that define how the U.S. government builds and operates technology
  • Become part of a network of AI-native engineers operating at the leading edge of public sector innovation

If you are prepared to be assessed on what you deliver — not your academic background — submit your application now.

What you will be doing

  • Deliver production-ready AI applications weekly under firm deadlines
  • Develop with contemporary AI-first methodologies (agents, tool use, evals, retrieval, deployment)
  • Engage and compete with leading engineering talent in a feedback-intensive environment
  • Address genuine, ambiguous problem domains similar to those found in government and enterprise settings
  • Convert authentic briefs into scoped, dependable, deployable systems

What you will NOT be doing

  • Attending theoretical lectures or passive instruction — every hour centers on building and deploying
  • Waiting months for your work to reach production — you will deploy functional systems each week
  • Depending on credentials, institutional pedigree, or interview outcomes to secure your placement — your production output is the sole evaluation criterion
  • Operating in a low-stakes environment — the systems you construct are subject to genuine security and reliability requirements

Key responsibilities

Deliver production-grade AI systems under real-world constraints that validate readiness 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

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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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Cognitive 
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Cognitive 
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Prove real-world 
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Accept job offer.
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What you will learn

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

  • AI-first development workflows (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector databases
  • Rapid project sprints focused on shipping under constraints

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

  • Agent systems, evals, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-grade delivery: QA, reliability, and high-standards execution
  • Fine-tuning + deployment patterns (LoRA/QLoRA + production integration)
  • Multi-agent modernization of real-world codebases
  • Multimodal AI builds (image/video/voice) and scalable infrastructure (AWS/Azure)

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