Istanbul, Türkiye
I’m an AI R&D Engineer and researcher focused on applying AI in FinTech and Software. My goal is to turn research into measurable outcomes by following an end-to-end workflow: literature → hypothesis → experimentation → PoC/prototype → productization. How I work: Clear problem framing, literature review, and hypothesis-driven development Rigorous evaluation and benchmarking (accuracy, latency, cost, safety/security) Rapid PoC & prototyping with modern architectures and tools, then integrating with product teams Engineering for performance, security, scalability, and architectural risk management Strong documentation, knowledge sharing, mentoring, and contributing to a sustainable R&D culture Leading digital transformation projects, TUBİTAK and Europe Interests: Deep learning, Machine Learning, LLMs, AI agents, Explainable AI, MLOps, LLMOps, Federated/Transfer Learning, RAG, AI Security model evaluation and improvement, and building trustworthy AI systems for financial products. I enjoy producing and sharing technical work: articles, talks, research outputs, and innovation/patent-driven deliverables. Open to collaboration on applied AI, R&D partnerships, and production-grade AI systems.
R&D Department | Oct 2024 – Present Shaping the company-wide AI and R&D strategy; translating emerging technologies into board-ready product opportunities Leading zero-to-one product initiatives from market discovery and scientific validation to go-to-market readiness Building and mentoring high-performing R&D teams; establishing a culture of research excellence and delivery discipline Championing enterprise-wide technology transformation with measurable business impact R&D Researching Projects: Principal Investigator across TÜBİTAK 1005, 1501, 1507, 1832 and 1833 programs, KOSGEB R&D and Innovation support schemes, and European Union Horizon-class funding instruments Leading R&D proposal authoring across TEKMER, Teknokent, Dijital Park and incubation ecosystems; positioning projects for maximum scientific and commercial merit Owning the full grant lifecycle: strategic framing, technical proposal architecture, budget modeling, work package design, consortium formation and partner negotiation Representing the organization in TÜBİTAK expert panels, KOSGEB evaluation committees, reviewer defenses and high-stakes technical evaluations Converting research outcomes into commercial-grade PoCs, intellectual property and productized solutions Applied Artificial Intelligence: Architecting production LLM platforms: Retrieval-Augmented Generation, fine-tuning, model evaluation frameworks, cost and latency optimization at scale Pioneering agentic AI systems and multi-step autonomous workflows using Model Context Protocol (MCP) Designing enterprise reference architectures for LLMOps, DataOps and AIOps Leading model, vendor and infrastructure selection decisions; advising on GPU and compute strategy for advanced AI workloads Establishing evaluation, safety and governance standards for generative AI deployments
INFLEKS Operation (Core-Banking Product) | Oct 2023 – May 2025 • Converted complex stakeholder and regulatory needs into a prioritized JIRA backlog, mapping end-to-end data flows and release plans. • Led zero-downtime releases (app + SQL), executed manual test suites, and produced root-cause reports that drove rapid defect resolution. TÜRİB Project | Oct 2023 – Aug 2025 • Analyzing and tracking new features for TÜRİB Exchange. • Managing the central and shared web service integration process for capital market intermediary institutions (SPAK). • Preparing technical documentation for web service integration. • Handling cash transaction and money transfer flows. Software Testing & Automation Transformation Project (Testinium) | Jan 2024 – Jan 2025 • Led the rollout of Testinium-based testing and development workflows at İNFİNA, overseeing end-to-end project execution and stakeholder alignment. • Acted as the key liaison between QA, development, and business teams, helping to embed modern software-testing practices company-wide. • Guided teams in writing high-impact manual test cases. • Designed effort-and-quality measurement frameworks that improved test-case efficiency and visibility. • Currently spearheading an AI-driven test-automation initiative to elevate the project to the next level, reduce regression time, and boost release quality. (now)
• Training capital market, Financial literacy, Finance modules in capital markets, Trading • Operations in the financial app • Fund, Product architecture • Risk profile, reports, legal declarations • Business Intelligence and Analytics
CAPM
Leader of Content and Archive Department
Demand forecasting and production planning decision support system The aim was to create a decision support system that accurately forecasts demand and efficiently plans production. The methods used include Theil's U method, ARIMA and SARIMA models for forecasting accuracy, and a comprehensive mathematical model for production planning that incorporates various constraints and parameters. The project required thorough analysis, literature review, error analysis, and model development to optimize production levels, reduce operational costs, and enhance overall efficiency. In the implementation phase of our demand forecasting system, we integrated machine learning and deep learning algorithms, specifically RNN and LSTM, to tackle the complexities of time series data and its evolving dynamics. For enhancing our forecast model, we meticulously evaluated various independent variables, subsequently incorporating them into ARIMAX and SARIMAX methods. This approach not only fine-tuned our forecasting accuracy but also allowed us to conduct an in-depth analysis of the models' error rates and regression, leading to more precise and reliable production planning strategies.
Test Automation and Security Solutions Department During my internship at NETAŞ within the Test Automation and Security Solutions Department, I gained hands-on experience in QA engineering and test automation. My responsibilities included working with tools such as Gradle and Maven, as well as utilizing DemoQA for testing processes. I contributed to various Selenium-based projects, implementing solutions in both Python and Java. This role allowed me to develop a strong foundation in QA testing methodologies and automation tools while enhancing my technical skills and problem-solving abilities.