I design scalable systems, build full-stack products, and help engineering teams turn complex requirements into reliable software.

• 💻 I have been coding for 7 years, including 3 years of full-time professional experience.
• 🧭 As a Tech Lead, I guide technical direction, system architecture, engineering standards, and delivery.
• 🛠️ I build end-to-end products with React / Vue, Node.js / NestJS, and Python / Django.
• 🧩 I enjoy designing distributed systems, monorepos, shared UI systems, and reusable application foundations.
• ☁️ I work with managed platforms and cloud services including AWS, Amplify, Convex, and Firebase.
• 🇹🇷 Based in Türkiye and open to collaborating on meaningful web products.

• Translate business needs into scalable system designs, technical plans, and clear delivery paths.
• Create architecture, system, sequence, and integration diagrams to make complex flows understandable.
• Evaluate trade-offs across frontend, backend, data, cloud services, performance, and maintainability.
• Establish engineering standards through code reviews, reusable patterns, testing practices, and technical documentation.
• Mentor developers, distribute ownership, remove technical blockers, and keep teams aligned.
• Identify technical risk and debt early while balancing long-term architecture with product delivery.

• Design durable, long-running workflows with retries, timeouts, idempotency, compensation, observability, and failure recovery in mind.
• Build workflow orchestration and automation solutions with Temporal, Conductor OSS, and n8n.
• Design authorization models using RBAC, ABAC, and ReBAC, choosing the right approach for the domain instead of forcing a single model everywhere.
• Work with centralized policy and permission systems such as Permit.io, AWS Verified Permissions, and Cerbos.
• Model resources, actions, relationships, and contextual attributes while keeping permission checks consistent across frontend and backend boundaries.

• Use Claude Code and OpenAI Codex as part of the engineering workflow for planning, implementation, debugging, refactoring, code review, testing, and documentation.
• Design reusable skills, agentic workflows, and scheduled automations that reduce repetitive work and improve engineering throughput.
• Apply prompt engineering through clear context, constraints, examples, task decomposition, and explicit verification criteria.
• Build human-in-the-loop workflows where AI accelerates delivery while technical decisions and output quality remain reviewable.
• Turn recurring engineering practices into repeatable AI-assisted processes instead of relying on one-off prompts.

AWS: Amplify, API Gateway, S3, and managed cloud services · Firebase: Analytics and platform integrations

Faber est suae quisque fortunae.