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Location
Hybrid (Cyprus)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 29, 2026. First seen by Alion on Jul 13, 2026. Quadcode scores B on the Alion truth index.

Overview
Company
Impact
Profile match
All-in-one white label solutions for Forex, CFD, Crypto and Options Brokers. Start your own Brokerage Business from Scratch.

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. You'll join a small high-impact team where 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.

This role is hybrid, based 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
  • Hands-on experience building multi-agent systems or workflows 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.)
  • Fluent Russian.
  • 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.
  • Sick leave without medical certificate: 3 days per quarter.
  • Catered lunches in the office.
  • Tuition reimbursement (kindergartens/schools).
  • Onsite Gym.
  • Corporate events and workshops.
  • Bonuses for special events (e.g., child's birth).
  • Birthday and anniversary gifts.
  • Company-provided laptop.
  • Corporate AI subscriptions (Claude, Gemini, GPT, etc.).
  • Access to a rewards marketplace offering products and language courses, redeemable using the company’s internal currency.
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