TL;DR

Senior Data Science Engineer (AI): Developing and applying predictive and generative AI models to enhance commercial performance and customer experience with an accent on Natural Language Processing solutions. Focus on scaling initiatives using RAG, architecting agentic AI systems, and collaborating with cross-functional teams to transition proof-of-concepts into production-ready deployments.

Location: Hybrid, North Macedonia

Company

%hirify_global% is a global organization providing business and tech advisory, enterprise solutions, product development, and software engineering services with a team of over 6,000 specialists.

What you will do

Develop and deploy predictive and generative AI models to solve commercial and customer experience challenges.
Scale existing AI initiatives using advanced techniques such as RAG, chunking, and agentic AI.
Collaborate with cross-functional teams to integrate models into production-ready systems.
Translate complex data insights into tangible business value.
Work on solutions utilizing LLM frameworks like Langraph, Langchain, or Llamaindex.
Support deployment of AI solutions across both cloud (AWS) and on-premises environments.

Requirements

Master degree in AI, Machine Learning, or Data Science.
3-6 years of professional experience as a Data Scientist.
Deep expertise in AI, Machine Learning, and LLM frameworks.
Proficiency in Python, SQL, and Git.
Knowledge of Agentic AI, vector databases, and RAG systems.
Experience deploying AI solutions on AWS and on-premise infrastructure.

Culture & Benefits

Global environment with a diverse team spanning five continents.
Commitment to equal opportunity in recruitment and career development.
Focus on professional growth within a large, international organization.
Collaborative work culture involving interaction with non-technical customers and technical stakeholders.

Hiring process

Application review by the recruitment team.
Talent acquisition interview to discuss professional goals and company fit.
Technical interview focusing on expertise, problem-solving, and logic.
Potential customer interview to align with business requirements.