LLM Engineer
$200,000+ Offers For Graduates $200,000+ Offers For Graduates 

3 weeks remote, 7 weeks onsite in Austin, TX
80–100 hours/week for 10 weeks
Short-term contract
Hybrid location
full-time (90 hrs/week)

LLM Engineer   $200,000+ Offers For Graduates $200,000+ Offers For Graduates 

Description

Gauntlet is a selective, fully funded 10-week fellowship designed for experienced engineers who are ready to prove their ability to build and deploy production-quality AI systems under demanding, real-world conditions. Fellows deliver weekly shipments, collaborate with seasoned operators, and gain firsthand access to founders, CTOs, and hiring partners.

Participants in our latest cohort generated over 300 first-round interviews with hiring partners. We aim for every graduate to secure offers from our partner network, with starting compensation no lower than $200,000.

The fellowship spans 10 weeks: the first 3 weeks are conducted remotely, and the remaining 7 weeks take place onsite in Austin, Texas. Fellows should anticipate a rigorous schedule—80 to 100 hours per week—structured to optimize learning velocity, tangible output, and professional advancement.

Program Outcomes:

  • More than 10 production AI applications delivered throughout the fellowship
  • Entry into Gauntlet's alumni and hiring partner network
  • Job offers of $200,000 or more from hiring partners for program graduates

If you ship quickly, thrive under pressure, and want your work—not your credentials—to define your next opportunity, apply today.

What you will be doing

  • Deliver production-ready AI applications weekly, meeting strict deadlines
  • Develop systems using modern AI-native workflows, including agents, tool integration, evaluation frameworks, retrieval mechanisms, and deployment pipelines
  • Work both collaboratively and competitively with elite engineering peers in a high-feedback setting
  • Present your builds directly to CTOs, founders, and hiring partners
  • Convert real project briefs into scoped, dependable, deployable systems

What you will NOT be doing

  • Spending multiple weeks on theoretical concepts, tutorials, or passive study without shipping working code
  • Creating prototypes that are never subjected to real-world usage or scrutiny
  • Focusing on resume formatting and portfolio curation instead of building and deploying functional systems
  • Enduring weeks of lectures and coursework before engaging with production code

Key responsibilities

Build and ship production-quality AI systems on a weekly cadence, transforming demonstrated engineering capability into career outcomes valued at $200,000 or more through Gauntlet's hiring partner network.

Candidate requirements

  • At least 3 years of professional engineering experience, or demonstrated equivalent capability
  • Must have independently designed, built, and deployed a minimum of one functioning software system to production or to real users
  • Highly responsive to feedback and capable of sustaining extreme execution intensity
  • Authorized to work in the United States without requiring visa sponsorship
  • Able and willing to commit to 80–100 hour work weeks and relocate to Austin for 7 weeks

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.

Frequently asked questions

About Crossover

What you will learn

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

  • AI-native development workflows, including coding agents, MCP, and real-time collaboration tools
  • Retrieval-Augmented Generation (RAG), vector databases, and embeddings
  • Fast-paced project sprints centered on shipping under tight constraints

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

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

Meet some people who've landed similar jobs

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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