I am pursuing a Master's in Software Engineering of Distributed Systems at KTH while building applied AI systems across search visibility, business understanding, and automation. My work combines backend engineering, distributed systems, and product thinking to create tools that help organizations improve how they operate, communicate, and appear in AI-generated answers.
I am a software engineer and master's student at KTH Royal Institute of Technology, specializing in Software Engineering of Distributed Systems. My current work is centered on building practical AI systems that turn complex business and digital signals into actionable insight.
I am the founder and builder of IntelliCite, an Answer Engine Optimization (AEO) platform that is also the focus of my master's thesis. Through IntelliCite, I have designed a full pipeline that evaluates how businesses are represented in AI-generated answers, identifies visibility gaps, generates improvement recommendations, and tracks performance over time using large-scale prompt testing based on realistic user search behavior.
In parallel, I work as an AI consultant on BrandBrain, where I contribute to building a system that can understand a company's brand, internal knowledge, and workflows. The goal is to create context-aware AI support for internal work while preserving brand consistency and improving organizational efficiency.
Earlier, I worked as a Client Software Support Associate at Relesys, partnering with enterprise customers to resolve technical issues, understand operational needs, and communicate clearly across technical and non-technical stakeholders. That experience strengthened my client understanding, technical communication, and ability to translate product complexity into practical solutions.
Built an AI-driven AEO platform that evaluates how businesses appear in AI-generated answers, analyzes site and content quality, generates prioritized recommendations, and monitors citation performance across realistic prompt sets. The work combines product design, systems thinking, experimentation, and measurable business-focused analysis.
Contributing to an AI platform designed to understand a business across brand, internal knowledge, and workflows. My work supports how business context is structured, interpreted, and used in an AI product intended to improve internal work, knowledge access, and brand-aligned output.
Worked closely with enterprise customers to troubleshoot technical issues, investigate platform behavior, and communicate solutions clearly across technical and non-technical stakeholders. The role required strong customer relations, client understanding, and collaboration with QA, product, and integration teams to improve reliability and customer outcomes.
Built strong communication, adaptability, and problem-solving skills through fast-paced service roles, with a consistent focus on professionalism, customer experience, and handling high-pressure situations effectively.
Advanced studies in scalable and reliable software systems, with current thesis work focused on AI search visibility, Answer Engine Optimization, and applied evaluation frameworks for how businesses are cited in AI-generated answers.
Developed a strong foundation in software development, systems thinking, digital products, and technical problem-solving across both design-oriented and engineering-oriented work.
Designed and built an Answer Engine Optimization (AEO) platform focused on how businesses are represented in AI-generated answers. IntelliCite evaluates website content and structure, identifies visibility gaps, generates prioritized recommendations, and monitors performance over time by testing large sets of realistic user prompts where a business should be cited or surfaced.
As part of my master’s thesis, I am running the full pipeline on a real business environment, covering website evaluation, AI perception analysis, recommendation generation, and citation tracking across AI answer systems. The project combines applied AI, systems thinking, product design, and measurable business impact.
Contributing to the development of an AI platform that can learn and understand a business, including its brand, internal knowledge, and working processes. The goal is to create a system that supports both internal operations and external brand consistency through context-aware AI assistance.
My work includes shaping how business context is structured, interpreted, and made useful inside an AI-driven product. This project sits at the intersection of software engineering, knowledge systems, and applied AI for real organizational use cases.
Built data collection and automation pipelines for platforms including Foodora, Wolt, and Uber Eats. These systems gathered live deal and platform data, transformed it into structured outputs, and exposed the results through APIs and JSON feeds for downstream applications.
The work involved session handling, anti-bot considerations, reliability improvements, and pipeline efficiency. The result was a set of practical systems for continuously collecting and operationalizing external data in production-oriented workflows.
Developed backend solutions in Java across both academic and personal projects, including algorithm-heavy systems and distributed systems assignments. The work focused on writing reliable, maintainable backend code with attention to scalability, performance, and correctness.
Key areas included concurrency, service design, algorithm implementation, and problem decomposition. These projects strengthened my ability to build robust backend systems and reason about performance under real technical constraints.
Worked on projects involving distributed systems, fault tolerance, replication, and performance optimization. Hands-on experience includes parallel and high-performance computing with technologies such as MPI, OpenMP, and GPU offloading.
These projects focused on designing systems that remain efficient and reliable under scale, while building a strong understanding of coordination, workload distribution, and computational performance across modern distributed environments.
Designed and developed web applications with React and Tailwind CSS, with a strong focus on usability, responsiveness, and maintainable architecture. Projects included product-oriented interfaces such as a deal aggregation platform and an AI-driven workout generator.
My frontend work is grounded in building interfaces that are not only functional, but useful and easy to navigate, with clear attention to user needs, fast iteration, and clean implementation.
Interested in collaborating, discussing AI systems, or connecting professionally?
This site is a static portfolio deployed via GitHub Pages. It is built and maintained by me, and the content reflects my current work across AI systems, software engineering, and product-focused technical projects.