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Текст:
Hirify AI/Оригинал
TL;DR
AI Engineer (FinTech): Building and deploying production-grade AI systems, intelligent agent pipelines, and Python services for chat, search, and retrieval use cases with an accent on RAG, vector databases, and scalable API development. Focus on evaluating and optimizing agent performance, deploying LLM inference pipelines, and establishing secure, compliant AI adoption across engineering teams.
Location: Limassol, Cyprus; hybrid model with 3 days from the office and 2 days from home. Working schedule: Monday to Friday, 09:00–17:00.
Company
hirify.global is a global trading and financial technology company with more than 15 years of experience and an international team.
What you will do
Design and deploy production-ready Python services using FastAPI to power AI capabilities.
Architect and fine-tune agent workflows for chat, search, and retrieval use cases.
Develop intelligent agents with LangChain, LangGraph, and LangSmith, including prompt engineering, integrations, and testing.
Integrate and optimize Qdrant, Milvus, and other vector databases for embeddings management, fast lookups, and hybrid search.
Evaluate, monitor, and optimize agent systems for reliability, accuracy, latency, cost efficiency, and horizontal scalability.
Collaborate with teams on AI adoption, integration of AI-powered tools, and optimization of coding-agent workflows using tools such as Claude Code and GitHub Copilot.
Requirements
3+ years of total software engineering experience, including strong backend development experience with Python.
1–2+ years of hands-on experience deploying and maintaining ML/AI systems in production environments.
Proficiency in Python and software engineering best practices, with a focus on clean, maintainable, production-quality code.
Experience with NLP, Retrieval-Augmented Generation (RAG), embeddings, and vector databases such as Qdrant or Milvus.
Deep expertise in LangChain and/or LlamaIndex for building agentic AI systems.
Strong experience with LangSmith, including evaluation, benchmarking, and tracing.
Experience with prompt engineering and systematic agent testing methodologies.
Strong understanding of LLM inference pipelines on local infrastructure and cloud platforms; proficiency with Docker and AWS, GCP, or Azure.
Ability to design clean, well-documented APIs and integrate them with microservices architectures.
Strong understanding of AI governance, security, compliance, and responsible AI practices, with the ability to establish and communicate clear AI adoption guidelines.
Nice to have
Hands-on experience deploying, configuring, and optimizing self-hosted LLMs with vLLM, Ollama, or SGLang.
Familiarity with open-source agentic coding harnesses such as OpenCode, OpenHands, or Cline, including enterprise workflow customization.
Culture & Benefits
Hybrid work with 3 office days and 2 home-working days per week.
22 days of annual leave, 12 paid sick days, and full medical insurance after 6 months.
Group Savings and Life Insurance Plan after 6 months.
Learning and development budgets, paid overtime, and referral bonuses.
Empathetic, respectful, and trust-based culture with team events, team-building activities, and Unwind Fridays.
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