Artificial Intelligence Engineer

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