Data & AI Engineer (LLMs, RAG)

TL;DR

Data & AI Engineer (LLMs, RAG): Build and deploy internal AI-powered systems and tools using Python, LLMs and RAG to support business decision-making. Focus on defining LLM evaluation metrics and benchmarking, fine-tuning prompt strategies, and integrating AI solutions into cross-functional operations with monitoring of LLM performance and costs.

Company

hirify.global develops web data gathering solutions for major global businesses.

What you will do

• Build AI applications using Python, LLMs and RAG.
• Research and apply new LLM technologies and frameworks, including AI coding assistants.
• Fine-tune and optimize prompt strategies to improve accuracy, reliability, and efficiency of LLM outputs.
• Define AI evaluation metrics and benchmarking frameworks; implement monitoring for LLM performance and costs.
• Collaborate with cross-functional teams to identify AI-driven opportunities and integrate solutions into operations.
• Promote adoption and understanding of AI within Oxylabs.

Requirements

• Proficiency in at least one programming language, ideally Python.
• Hands-on experience with agentic development patterns (tool use, planning loops, evaluation).
• Experience with LLMs and AI application development (e.g., Anthropic/OpenAI/Gemini APIs).
• Experience with cloud infrastructure (ideally Google Cloud or AWS).
• Knowledge of DataOps practices and tools: Git, Terraform, Docker, and CI/CD.
• Excellent communication in Lithuanian and English (written and spoken).

Culture & Benefits

• Hybrid work: 3 office days / 2 WFH, plus WFA options.
• Private health insurance, psychotherapy support, and on-site well-being consultants.
• 24/7 gym access and a wellness app.
• 40+ learning options, external conferences, mentorship, and year-round knowledge sharing.
• Team events, overseas workation, quarterly team-building budgets, and extra days off.
• Gross salary range: 3400–5600 EUR/month (open to discussion based on skills and competencies).

Hiring process

• Initial contact with the recruiter.
• Interviews to assess technical fit and communication skills.
• Discussion of role scope and compensation.