Description
You're not just an engineer—you’re an AI-native builder who can weave reasoning into software. If you’re obsessed with vibecoding intelligent systems, know how to weaponize LLMs for real-world automation, and you’ve got a telecom brain with Python hands, this one’s for you.
We’re rewriting how telecoms operate. Our Ontology platform isn't just AI-enhanced—it's AI-centered. We're building structured knowledge systems (ontologies) that unlock LLM automation across messy, siloed telecom infrastructure. This isn't about tossing a chatbot on top of your stack. It’s about embedding semantic intelligence into the core of network ops, provisioning, and CX—turning brittle workflows into self-improving, explainable, decision-making systems.
This role is not for AI tourists or traditional full-stack devs hoping to sprinkle some GPT on top. You’ll be building working proof-of-concepts that show enterprise clients what the future feels like—automated, fast, and scalable. You’ll write structured prompts that reason across OSS/BSS systems, train and fine-tune agents that actually get telco work done, and deploy real-time workflows that crush latency and manual effort.
You’ll be joining a small team with outsized technical credibility. You’ll own POCs from semantic mapping to model orchestration to deployment, shortening sales cycles and opening the door to deeper platform integration. If you’re the kind of engineer who codes like a designer, speaks LLM like a second language, and gets a dopamine hit from watching an AI agent solve a real workflow without human help—apply now!
What you will be doing
- Build and deliver AI proof-of-concepts that show how Ontology AI can solve real problems for telecom clients. Ontology AI means teaching AI systems to understand the structure of telecom — how data, systems, and workflows are connected — so they can reason more intelligently.
- Develop core platform modules that let the AI map meaning across telecom data, follow instructions, and coordinate actions across systems.
- Design and deploy AI models that make smart, real-time decisions in telecom scenarios like network operations, service provisioning, and customer experience.
What you will NOT be doing
- Traditional software development focused only on manual coding and maintenance.
- Basic API development or standard telecom software engineering without AI enhancements.
- AI used as a novelty tool without direct impact on telecom efficiency.
Key responsibilities
- Build systems aimed at enhancing technical credibility with clients, shortening sales cycles, and increasing opportunities for deeper platform integration.
Candidate requirements
- At least 3 years of experience in a software engineering or architecture role
- Advanced proficiency in Python
- Experience in DevOps automation, as well as strong Kubernetes and AWS skills
- Experience in telecommunications system integration and automating telco-specific workflows
- Experience using AI tools, such as Cursor and LLM copilots, for rapid prototyping
- Deep understanding of vector databases and RAG techniques
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.
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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.
