Technology & AI leader
I design data and AI solutions
and lead the teams
that build them.
Operating models that connect technology to business outcomes, and commercial growth.
Connecting technical credibility, commercial targets and the partner network; approaching growth at regional scale, beyond any single customer.
View this experienceBuilding teams, developing talent and making AI part of everyone’s work.
Turning individual technical output into team capability; demonstrating model success through concrete results in maintenance operations.
View this experienceScalable platforms with manageable costs across on-premises and cloud environments.
Evaluating a large-scale platform change beyond the technical migration, by the query times users expect.
View this experienceFrom idea to production system: enterprise AI architecture and agentic AI.
Evaluating model choice within the full production system; addressing flexibility and control in the same architecture.
View this experienceMaking AI safe, measurable and auditable.
Gaining speed in a controlled banking process while addressing the data pipeline and report integrity together.
View this experienceData analysis, solution architecture
and AI team management.
Meeting growing GenAI demand required the team capacity and resourcing model to take the architecture into production. A structure that allocated resources project by project was limiting capacity.
I built the AI Capability team from my architectural vision and made seven hires. I lead this team directly, and the AI CoE squad as chapter lead in a PO-driven matrix structure; 20+ people across the two teams. I moved to a shared resource pool, managed prepaid cloud commitments and led the go-live of 542 IVR. I manage a multimillion-dollar annual AI budget and, as a member of the GenAI Design Authority, report monthly to senior leadership.
The resource pool delivered roughly 30% capacity gain; cloud commitments saved roughly $300–400K. The 542 IVR coordinator handles 100K+ calls a month, with 218K+ calls in roughly the first two months. About 23% of tariff recommendations convert into approved sales leads: 1,000+ leads. Work the teams contributed to includes VHub, TOBi, CX Insight, AQM, GenAI Ops for IT and GuardLine AI.
My leadership directionCombining team building, matrix leadership, capacity planning, budget discipline and production ownership; measuring capacity, cost and customer engagement results separately.
A post on our tariff agent in live use: it understands customer needs, recommends tariffs and manages the process from approval to activation.
LinkedIn post ↗Post ·Our GENAI for IT Ops team was runner-up for the MEA region at the 2026 CSP awards. I contributed as the manager supporting the team.
LinkedIn post ↗Post ·After winning the European championship, our team advanced to the Global Final.
LinkedIn post ↗Post ·Team work that started as Chat with Your Data went live internally as VHub.
LinkedIn post ↗Post ·In customer-facing agentic AI, the core design question was how much decision freedom to give the LLM and where deterministic business rules should take over.
I designed the 542 IVR architecture to work with different models across on-premises and cloud environments. I built RAG-based access to enterprise knowledge, business rules and security controls into the agent flow. I treated quality evaluation and observability as part of the service-based production architecture.
This laid the architectural and engineering foundation for 542 IVR, which I would later take live as a manager. Business rules, security, evaluation and observability became part of the design.
My leadership directionEvaluating model choice within the full production system; addressing flexibility and control in the same architecture.
From my attendance at Gartner IT Symposium.
LinkedIn post ↗Post ·43 teams, 182 participants and 8 finalists. Throughout the process, we supported the teams’ use of GenAI with five training sessions and panels.
LinkedIn post ↗Post ·Enterprise customers needed different architectural solutions for data loading, query performance and infrastructure costs. I addressed these needs together with the sales teams’ commercial targets.
I led solution architecture with account teams covering Türkiye, Central and Eastern Europe, and the UAE. My customer work during the Vertica years included the BTK hybrid lakehouse, the İşbank open banking data warehouse, Sahibinden’s cloud-based disaster recovery/data lake designs, the SunExpress SAP→Azure migration, and data warehouse optimization for an insurance company in Poland.
Together with the account team, we closed roughly $10M in business against a total quota of $6.1M, reaching about 164% quota attainment; 320% in the best year. Customer engagement results: 78% faster data loading at BTK, roughly 45% faster queries at İşbank, 65% lower total cost of ownership in the first year at Sahibinden; and a 60% capacity increase in the data warehouse in Poland. President’s Club and Solution Architect of the Year (FY23–FY24).
My leadership directionEvaluating customer requirements, architectural choices and commercial outcomes in one frame; a solution approach that creates measurable value across different organizations.
My talk on big data and analytics in Warsaw. Event: 22 October 2024.
LinkedIn post ↗Post ·From the summit where we hosted more than 1,000 attendees. Our customers shared their data and analytics work on stage.
LinkedIn post ↗Post ·Talks at more than 25 industry events in Türkiye and Eastern Europe; Presales of the Year and President’s Club recognitions.
LinkedIn post ↗Post ·Growing Vertica in Türkiye, Central and Eastern Europe, and the UAE required sales and partner work to move forward together with solution architecture grounded in customer needs.
I took on both business development and solution architecture for the region. Working with account and partner teams, I grew the customer base and the partner ecosystem.
In FY22, I reached 125% of quota; the partner ecosystem grew by 70%. The customer count in Türkiye tripled, and the license revenue share rose from 3% to 10%. I received the Top FY22 Presales/SA International Region recognition.
My leadership directionConnecting technical credibility, commercial targets and the partner network; approaching growth at regional scale, beyond any single customer.
Customers needed a data science capability that could solve problems as different as credit risk and heavy equipment maintenance.
I built and managed a three-person data science team. I worked on risk scoring optimization for a retail loan portfolio and a predictive maintenance model for heavy equipment.
The predictive maintenance model reduced equipment downtime by 40%; the team I built delivered machine learning use cases to customers.
My leadership directionTurning individual technical output into team capability; demonstrating model success through concrete results in maintenance operations.
On the data platforms of banking and public-sector customers, queries stretching to twenty-four hours had become a performance barrier for the business.
I led a 2.3 PB data migration from MSSQL to Vertica. I worked on big data architecture, risk data marts and ETL automation for customers.
Through the data migration, I cut query time from twenty-four hours to five minutes.
My leadership directionEvaluating a large-scale platform change beyond the technical migration, by the query times users expect.
Data governance in banking required tracking branch-level data quality issues and preparing datasets that analytics teams could use.
I developed ML models to predict data quality issues. I queried and transformed large datasets in the data warehouse with SQL and Python, and worked on the Yapı Kredi data governance program.
I produced models to predict data quality issues and transformed datasets for analytics teams to use.
My leadership directionConnecting governance to day-to-day data engineering and analysis; preparing data for downstream teams.
In the Legal and Regulatory Reporting team, preparing BDDK (BRSA) reports took eight hours. The same data flow also fed treasury and liquidity reporting.
I was selected for the bank’s Management Trainee program. I redesigned the ETL flows and intermediate layers of the BD111 and LK120 reports and consolidated more than 20 regulatory reports.
I cut processing time for BDDK (BRSA) reports from eight hours to thirty minutes and improved the data pipeline feeding treasury and liquidity reports.
My leadership directionGaining speed in a controlled banking process while addressing the data pipeline and report integrity together.
At the construction company, tracking cash flow, profit and loss, and the balance sheet required regular financial reports built from transaction data.
I prepared daily, weekly and monthly financial reports from OLTP data. I validated data loading and cleansing flows and performed clustering analysis on customer data.
I produced regular reports supporting financial tracking, along with analytical outputs for customer segmentation.
My leadership directionLinking data quality to the usability of financial reports; translating technical analysis into the business unit’s decision needs.
Serving as a reserve officer in the Turkish Land Forces meant working within a military unit’s command structure and taking on team responsibility.
I served as a platoon commander as a reserve officer.
It added the experience of carrying command responsibility in a military unit to my career.
My leadership directionDirect team responsibility and mission discipline within a command role.
I worked on the Saudi Aramco project as part of an international team. Site material inventories and the financial data flow between offices required regular reporting.
I prepared construction material inventory reports and coordinated the financial data flow between the Saudi Arabia and Istanbul offices. I produced weekly reports on data quality and system availability.
I delivered inventory reports for procurement planning and site logistics, along with a consistent financial reporting flow between offices.
My leadership directionApproaching data work through site operations and the shared needs of teams in different countries.
