Description
Elite Java Developers Only: Where AI-Driven Engineering Redefines What's Possible
You're an engineer who doesn't tolerate bad code, slow deployments, or outdated development practices. You don't just write software—you build AI-driven systems that make traditional engineering look sluggish and inefficient. If that sounds like you, keep reading.
Most software teams are still writing code the old way—manual debugging, trial-and-error deployments, and features that barely leverage AI beyond a sprinkle of Copilot suggestions. Trilogy is different. Every part of our development process is infused with AI: feature ideation, bug detection, defect resolution, and performance optimization. This isn't about dabbling in AI tools; this is about fully integrating AI into the software lifecycle to eliminate waste, ship faster, and build with precision.
In this role, you will take existing B2B products, break them down, rebuild them as cloud-native applications, and optimize them with AI at every level. You'll be developing and deploying AI-powered features, using cutting-edge retrieval-augmented generation (RAG) for automated defect detection, and ensuring every release is smooth—zero outages, zero disruptions, zero excuses. If you're looking for a job where you spend weeks debating architecture decisions instead of shipping, this isn't it.
If you're ready to push the boundaries of AI-driven software engineering and accelerate your career into high-scale cloud-native development, apply now. If you prefer sticking to what you already know, writing test cases by hand, or working in teams that are afraid of automation, this isn't for you.
What you will be doing
- Harness advanced analysis tools and RAG vector stores to systematically identify, diagnose, and eliminate product defects with precision and speed.
- Architect and deploy AI development agents to design and implement innovative features that transform cloud-native applications.
- Drive excellence through collaboration with our global engineering team, delivering enterprise-grade solutions that exceed expectations.
What you will NOT be doing
- Routine Monotony: We've eliminated cumbersome infrastructure tasks so you can focus exclusively on creating innovative solutions that matter.
- Endless Meetings: Your expertise is wasted in meeting rooms. Here, you'll spend more time coding and less time talking about coding.
- Manual Testing: We leverage AI-powered testing frameworks, not tedious manual verification processes that waste engineering talent.
Key responsibilities
Transform enterprise software through AI-driven innovation, delivering features that streamline workflows and empower service providers with tools that create measurable business advantage.
Candidate requirements
- AI-First Engineering Mindset: You must approach problems with AI as the foundation of your solution strategy, not merely as an enhancement tool.
- 4+ years of professional experience in commercial Java development, with demonstrable focus on production-grade server-side web applications.
- Proven expertise using GenAI code assistants (Github Copilot, Cursor.sh, v0.dev) in professional environments.
- Documented success implementing Generative AI solutions with quantifiable business impact.
How it works
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.
STEP 1
Pass Cognitive Aptitude Test.
STEP 2
Pass English Proficiency Test.
STEP 3
Prove Real-World Job & AI Skills.
STEP 4
Ace An Interview Or Two.
STEP 5
Accept Job Offer.
Frequently asked questions
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Why Crossover
Recruitment sucks. So we’re fixing it.
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
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
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.
