AI Engineer

Quadcode; Georgia; Hybrid; USD 120,000 - 180,000; Full time

Job summary

Quadcode seeks an AI Engineer to join its AI Platform team, focusing on designing, building, and maintaining production generative AI pipelines and LLM-powered features that often handle financial and trading data.

You will work on agentic systems with MCP integrations, implement backend services in Python atop OpenAI/Anthropic/xAI APIs or on-premise deployments, and refine prompt engineering and evaluation pipelines for reliable production systems.

Qualifications

• Production LLM features shipped with OpenAI and/or Anthropic or on-premise models.
• Hands-on multi-agent systems development and MCP server experience.
• Proficient Python with API design, databases, Docker, and version control.
• Experience with structured outputs, prompt evaluation, and cost-aware design.
• English fluency in written and spoken communication.

Responsibilities

• Design, build, and maintain LLM-powered features and pipelines for generative AI products, including systems that process financial and trading content.
• Develop and improve agentic systems and multi-agent workflows, including MCP server integrations.
• Implement production-grade backend services in Python on top of LLM provider APIs and/or on-premise deployments.
• Build and iterate on prompt engineering and evaluation pipelines with structured outputs and validation.
• Convert prototypes into reliable, maintainable production services.
• Monitor LLM cost, latency, and reliability trade-offs across end-to-end pipelines.
• Collaborate with a senior AI Platform team on architecture, code review, and technical direction.

Skills

Production LLM experience

Multi-agent workflow experience

Python proficiency

LLM engineering skills

English fluency

Tools

REST APIs

SQL

Docker

Git

Concurrency

Job description

Quadcode is seeking an AI Engineer to join its AI Platform team. The role focuses on designing, building, and maintaining production generative AI pipelines and LLM-powered features, frequently involving financial and trading data.

Key Responsibilities

• Design, build, and maintain LLM-powered features and pipelines for generative AI products, including systems that process financial and trading content
• Develop and improve agentic systems and multi-agent workflows, including integrations via MCP (Model Context Protocol) servers and tooling
• Implement production-grade backend services in Python on top of LLM provider APIs such as OpenAI, Anthropic, and xAI, and/or on-premise LLM deployments
• Build and iterate on prompt engineering and prompt-evaluation pipelines, including structured output generation and validation
• Convert prototypes and proofs of concept into reliable, maintainable production services
• Monitor and manage trade-offs across LLM cost, latency, and reliability for end-to-end pipelines
• Work closely with a small, senior AI Platform team on architecture, code review, and technical direction

Requirements

• Production LLM experience: shipped real, live features using OpenAI and/or Anthropic APIs, or with on-premise/open-weight LLMs, not limited to experiments or side projects
• Multi-agent workflow experience: hands-on development of multi-agent systems or workflows and work with MCP servers
• Strong Python and software engineering foundations (2 to 4+ years), including REST APIs, SQL, Docker, git, and concurrency, plus demonstrated ability to move from prototype to maintainable production service
• Practical LLM engineering skills including structured outputs, prompt evaluation, and cost-aware design decisions in real environments
• English fluency in both written and verbal communication

Technologies

• Python
• OpenAI, Anthropic, xAI
• MCP (Model Context Protocol)
• REST APIs, SQL, Docker, git
• Open-weight LLMs, on-premise LLMs
• Kubernetes, Kubeflow, Airflow
• Hugging Face inference
• AWS, GCP

Location and Experience

Location: Georgia (hybrid). Minimum experience: 2 years.

Benefits

• Hybrid work model in a 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 & 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 with products and language courses, redeemable using the company’s internal currency

Nice to Have

• Prior experience working in fintech
• Finance and 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, including 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