Artificial Intelligence Engineer

Job Description

We are looking for an Artificial Intelligence Engineer who will take an active role in AI, data analytics, and prediction projects, and who can develop end-to-end AI solutions without relying on RPA tools.

In this role, we expect a team member who can translate diverse business problems into data- and AI-driven models, process the right data using the right methods, and ensure that developed models are integrated into decision-making processes and enterprise systems.

We are seeking candidates with a Bachelor’s or Master’s degree in Computer Engineering or related fields, and a minimum of 5 years of experience in data engineering and/or software development.

Responsibilities

• Translate business needs from internal stakeholders into data-driven problem definitions
• Perform data collection, cleaning, feature engineering, and analysis
• Design and work with ETL / ELT processes and data pipelines
• Select appropriate models for regression, classification, time series forecasting, and anomaly detection
• Collaborate with internal stakeholders to analyze business processes and re-architect them using an AI-native automation approach
• Train, test, validate, and evaluate the performance of models
• Design and develop LLM-based AI and automation solutions
• Build solutions for document understanding, text processing, and intelligent classification using NLP, LLM, and RAG approaches
• (Preferred) Develop container-based services using Docker or similar technologies
• Integrate LLM and ML models into enterprise systems via APIs, services, and event-driven architectures
• Analytically design how model outputs translate into business decisions
• Report developed models, produce interpretable outputs, and maintain proper documentation
• Develop PoC (Proof of Concept) and pilot implementations when required
• Take AI projects from concept to production end-to-end
• Identify and improve performance bottlenecks, reliability issues, architectural constraints, and system design gaps
• Apply MLOps practices, including model versioning, monitoring, drift detection, and retraining workflows

Technical Qualifications

• Advanced development experience with Python
• Experience building AI- and software-driven automation solutions without using RPA tools
• Hands-on experience designing and developing LLM-based AI solutions
• Experience with OCR, document processing, or unstructured data pipelines
• Experience working with SQL and NoSQL databases
• Strong knowledge of NumPy, Pandas, SciPy, and related ML / NLP libraries
• Solid understanding of supervised and unsupervised learning and predictive modeling
• Experience with regression, classification, clustering, anomaly detection, and time series analysis
• Knowledge of model evaluation metrics (Accuracy, Precision, Recall, F1, RMSE, etc.)
• Ability to translate business requirements into technical AI automation solutions
• Strong analytical thinking and problem-solving skills
• Awareness of overfitting / underfitting and model improvement techniques
• Ability to design and implement RESTful, API-first integrations
• Understanding how model outputs integrate into business processes
• Awareness of data privacy regulations (KVKK / GDPR) and enterprise data security principles