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

Work arrangement
Yes