We're looking for an AI Engineer to join our AI Platform team, which builds and operates the generative AI pipelines powering our products, many of which involve financial and trading data, terminology, and specifications. This is a backfill role on a small, high-impact team, so you'll have real ownership from day one.
You'll work across our broader AI-platform portfolio: prompting and prompt evaluation, agentic systems, MCP tooling, and evaluation pipelines: writing backend Python on top of LLM providers like OpenAI, Anthropic, and xAI. This is an applied engineering role focused on shipping and maintaining production LLM systems, not a model-training or research position, prior training/research experience is not required.
This role is hybrid, with an expectation of at least 3–4 days per week in our Limassol office.
Tasks:
Design, build, and maintain LLM-powered features and pipelines for our generative AI products, including those handling financial and trading content
Develop and improve agentic systems and multi-agent workflows, including integrations using MCP (Model Context Protocol) servers/tooling
Write production-grade backend Python services on top of LLM provider APIs (OpenAI, Anthropic, xAI) and/or on-premise LLMs
Build and iterate on prompt engineering and prompt-evaluation pipelines, including structured output generation and validation
Take prototypes and proofs-of-concept and turn them into reliable, maintainable production services
Monitor and manage LLM cost, latency, and reliability trade-offs across pipelines
Collaborate closely with a small, senior AI Platform team on architecture, code review, and technical direction.
Requirements:
Production LLM experience: You've shipped real, live features using OpenAI and/or Anthropic APIs, or with on-premise/open-weight LLMs, not just experimentation or side projects
Multi-agent & MCP experience: Hands-on experience building multi-agent frameworks and working with MCP servers
Strong Python & software engineering fundamentals (2–4+ years): REST APIs, SQL, Docker, git, and concurrency, with a demonstrated ability to take projects from prototype to maintainable production service
Practical LLM engineering skills: Comfortable working with structured outputs, prompt evaluation, and cost-aware design decisions in real systems
English fluency (written and verbal).
Nice to Have:
Prior experience working in fintech
Finance/markets knowledge: tickers, earnings, technical indicators, forex/CFDs
Quant background
Experience with model fine-tuning/training, RAG, or LLM optimization techniques
Track record in Kaggle competitions focused on LLMs or multi-agent frameworks
GPU infrastructure experience: provisioning GPU compute or serving open-weight models (e.g., Hugging Face inference)
Experience with Kubernetes, Kubeflow, or Airflow
Data analysis and statistics experience
Experience with cloud platforms (AWS, GCP, etc.)
Russian language proficiency.
We know the combination of production LLM engineering and finance-domain knowledge is rare. If you're a strong AI/LLM engineer without a finance background, we still want to hear from you.
What we offer:
Hybrid work model in our brand-new office in Limassol
Health insurance and mental health services
13th salary and 21 vacation days per year
Catered lunches in the office
Tuition reimbursement (kindergartens/schools)
Training and Development opportunities
Onsite Gym
Corporate events and workshops
Bonuses for special events (e.g., child's birth).
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