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General Application Questions

• Do you have the legal right to work in the country where you reside?✱

  • Yes
  • No
• Are you based in the US?✱

  • Yes
  • No
• What is your notice period?✱
• How did you hear about this job opportunity?✱

  • Online job board
  • Company website
  • Referral from a friend or colleague
  • Social Media
  • Recruiter
  • Other
• Any additional files you think would be useful /Portfolio, Cover Letter, etc./.

  Upload file
• Which operating system do you primarily work with?✱

  • Windows
  • Mac OS
  • Linux

AI Engineer

• Are you currently based in Cyprus?✱

  • yes
  • no
• This role requires being in our Limassol office 3 days per week. Are you able to commit to this hybrid schedule?✱

  • Yes
  • No
• Do you have at least B2 (Upper-intermediate) in English?✱

  • Yes
  • No
• Have you shipped one or more production features (not prototypes or personal projects) using OpenAI, Anthropic, xAI, or open-weight/on-premise LLMs?✱

  • Yes
  • No
• Do you have hands-on experience building multi-agent systems and/or working with MCP (Model Context Protocol) servers?✱

  • Yes, both
  • Yes, multi-agent systems only (LangGraph, CrewAI, AutoGen, etc.)
  • Yes, MCP only
  • No experience with either
• Which of the following production engineering experience do you have? (Select all that apply)✱

  • I have built production backend services in Python (REST APIs, SQL, Docker, Git, concurrency), not just ML models or data pipelines.
  • I have personally taken AI/LLM solutions from prototype to production.
  • I have been responsible for deployment, monitoring, maintenance, and ongoing support of production AI/LLM services.
  • I have optimized production AI/LLM systems for cost, latency, reliability, or scalability.
• Which of the following areas do you have professional hands-on experience with? (Select all that apply)✱

  • Fintech / financial markets
  • RAG systems and LLM optimization (retrieval pipelines, embeddings, vector databases, reranking, LLM performance optimization)
  • Model fine-tuning / training (LoRA, PEFT, SFT, RLHF/DPO, training or adapting LLMs)
  • Open-source / on-premise LLM deployment (Llama, Mistral, Qwen, Gemma, Hugging Face models, local inference)
  • GPU infrastructure and LLM serving (GPU provisioning, vLLM, Triton, TensorRT-LLM, Hugging Face Inference)
  • Cloud platforms (AWS, GCP, Azure or similar)
  • Kubernetes / ML infrastructure (Kubernetes, Kubeflow, Airflow, ML pipelines)
  • Data analysis and statistics (statistical modeling, experimentation, analytics, data-driven decision making)
  • Quantitative background (mathematical modeling, quantitative research, financial modeling)
  • LLM/AI competitions or research projects (Kaggle, benchmarks, open-source contributions)
  • Russian language proficiency
• What are your salary expectations (gross EUR monthly)?✱

• • Yes, Quadcode can contact me about future job opportunities for up to 6 months
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