Enes Aydin

Primary Client: Apple • Contributed to MCP server–based evaluation workflows, supporting Function Calling and tool-augmented agent scenarios for more reliable LLM training and assessment. • Led AI data operations and quality calibration, managing a distributed team across multiple countries and locales (Turkey, Taiwan, China, Hong Kong) to deliver consistent, high-quality datasets for LLM training and evaluation (RLHF, agentic data, SFT). • Partnered with top-tier global clients on large-scale AI initiatives, maintaining a strong focus on precision, scalability, and real-world usability of datasets and evaluations. • Mentored and calibrated trainers through structured feedback loops, ensuring outputs aligned with client expectations, quality benchmarks, and project-specific guidelines. • Defined and enforced QA standards (rubrics, edge-case checks, sampling strategies), improving consistency across multi-locale annotation and evaluation streams. • Designed clear, repeatable workflows and lightweight tooling that simplified complex data processes, making execution faster, more accessible, and less error-prone. • Coordinated delivery across ops, reviewers, and SMEs, proactively unblocking issues and maintaining high throughput under tight timelines. • Combined strong stakeholder communication with hands-on technical execution to build reliable delivery processes that translated into measurable quality gains.

• Designed and optimized system prompts and user prompts to enhance AI Agent performance, ensuring clarity, consistency, and contextual accuracy. • Developed e-commerce–focused use cases tailored for Amazon Sellers, enabling the agent to handle product listings, customer queries, and marketplace operations autonomously. • Conducted integration tests with modern third-party applications such as Spotify and Google Maps, validating agent capabilities across multiple API environments. • Led prompt engineering experiments to identify the structure of an optimal user prompt and refine instruction hierarchies for reliable agent reasoning. • Implemented a dual-feedback framework combining third-person critic comments and first-person reasoning reflections to improve iterative learning efficiency. • Reduced hallucination rates and improved factual consistency by establishing structured reinforcement and correction workflows. • Optimized tool output validation to ensure data reliability and contextual accuracy across multi-tool chains. • Collaborated on assistant correction protocols to guide the agent through recovery paths and maintain stable output behavior. • Developed internal evaluation benchmarks and documented insights to improve workflow automation and large-scale agent training pipelines.

RAG & Hybrid Retrieval LLM Fine-tuning & Prompt Engineering Speech AI (TTS & ASR) AWS (MSK, Lambda, SQS, Kinesis, S3, EC2) Data Engineering & Warehousing Scalable AI Pipelines

- Actively participated in one of the company's largest IT investments, contributing to the complete renewal of the SuccessFactors (SF) system and taking part in the implementation of a brand-new, end-to-end (Full Cycle) SF solution from scratch. -Actively contributed to Employee Central (EC) and integrations, ensuring seamless system functionality. -Conducted requirement analysis and developed best practice-compliant solutions. -Managed data integrations between SF and Windows Active Directory, DWH, SAP ERP, and S/4HANA. -Created documentation for CPI and existing integrations, including API data specifications. -Defined EC from the ground up, configuring positions and organisational structures. -Worked closely with business units to gather requirements and coordinate necessary actions. -Handled cost centre and fund centre integrations, ensuring accurate data mapping. -Oversaw ticket management and provided internal support. -Researched SAP Global Best Practices and analysed related documentation. -Performed testing for EC and SAP’s AI-powered chatbot, Joule. -Served as a Prompt Engineer, executing and evaluating chatbot (Joule) performance tests. -Monitored daily RAID logs and worked within an Agile methodology framework. -I have general knowledge of recruitment, offboarding, onboarding, crossboarding, and compensation modules. -I was part of the project management team, and we followed the Agile methodology. -We managed the project through daily sprints. -I understood and analysed the business unit's requirements and directed the relevant consultants.

As one of the 30 people selected for this program from Turkey, SAP Young Professionals Program (YPP) helps me broaden my perspective and gain new professional skills. Beyond technical knowledge, I have been trained in soft skills such as communication and presentation, design thinking, and networking, by world-class training academies. • Selected as one of 30 trainees from all over Turkey • SAP Certified Associate – Business Process Integration with SAP S/4HANA 2020 • SAP Certified Specialist – Implementation Consultant – SAP S/4HANA Cloud Private Edition • Interview Techniques & Skills • Advanced Communication & Personal Leadership Workshop • Exploring AI + Managing Clean Core

Built and launched a Private Label business model, creating my own brand through Amazon Brand Registry in the USA. Managed the end-to-end supply chain, from sourcing and manufacturing in Asia to selling in the US market. Oversaw Amazon Advertising campaigns, optimizing ROI and sales growth. Implemented SEO strategies to increase product visibility and organic rankings on Amazon. Handled the entire process independently, ensuring brand growth and operational efficiency.

I worked as a Business Developer at My Car. I managed tasks such as inventory tracking, warehouse management, purchasing, and data processing in ERP. I organized weekly sprints to lead team collaboration. Working with team members from different countries provided me with unique experiences.

I completed my internship as a business analyst in the R&D project delivery team. I actively participated in the ACEP project, where I created MMC documents and made mockup drawings. I processed and organized various data in Excel and followed SDLC processes. Additionally, I executed SQL queries.

I interned in the R&D and Innovation department where I created regular workflows in Jira to organize weekly sprints within the Agile methodology framework. We developed various MVPs. This experience provided me with insights into business analysis and project management.

We implemented our projects designed during a 12-week educational process with our middle school students. We produced parts designed in Fusion 360 using CNC laser and 3D printers. We actively utilized the Design Thinking method.

I completed an English language course in Australia, where I had the opportunity to immerse myself in different cultures and make many new friends. This experience not only improved my language skills but also broadened my global perspective.

1st Semester Coursework: • Fundamentals of Artificial Intelligence and Data Engineering • Natural Language Processing (NLP) • Data Mining and Analysis • Next Generation IoT Applications • Research Methods • Orientation to Graduate Studies​​​​​​​​​​​​​​​​

Honor Student 🏅 GRADUATION PROJECT AND THESIS: WAREHOUSE LOCATION SELECTION BY FUZZY MULTI-CRITERIA DECISION-MAKING AND MACHINE LEARNING

Dropped Double Major