Tech stack
In my commercial work, I most often use a combination of Node.js and TypeScript, which form the foundation of my development toolkit. In my free time, I enjoy experimenting with Go, creating personal projects and tools with a focus on simplicity and high performance. In the past, I have also worked with Python, mainly in the context of microservices as well as data processing and analysis. This allows me to select the right language and technology to match the specific problem – not the other way around.
Technologies:
My primary backend framework is Nest.js, which I use to build microservice-based applications and asynchronous communication systems using message brokers (e.g., RabbitMQ). Depending on the needs, I also work with other communication patterns such as RPC or real-time connections via sockets.
When required, I develop serverless solutions, often based on AWS Lambda. I have experience working with both relational and non-relational databases, particularly MongoDB and Redis, as well as full-text search engines like Elasticsearch.
Technologies:
I have been exploring artificial intelligence and its applications in software development for some time now. I’m particularly interested in integrating AI models into backend systems and leveraging them to support and automate processes within applications. I experiment with tools like LangChain and Ollama, as well as approaches such as RAG and Agentic AI.
I also use AI tools daily for writing code, creating tests, and producing documentation. This speeds up my work and allows me to focus on other creative and high-value tasks.
Technologies:
In both my professional and personal projects, I aim to design solutions that are cloud-ready from the very beginning. I most frequently work with AWS, Docker, and the Infrastructure as Code approach using Terraform.
I regularly work with CI/CD pipelines, mainly using GitLab CI and GitHub Actions, and occasionally Jenkins. Currently, I’m expanding my knowledge of Kubernetes and advanced AWS services to create even more scalable and fault-tolerant systems.
Technologies:
In my commercial work, I most often use a combination of Node.js and TypeScript, which form the foundation of my development toolkit. In my free time, I enjoy experimenting with Go, creating personal projects and tools with a focus on simplicity and high performance. In the past, I have also worked with Python, mainly in the context of microservices as well as data processing and analysis. This allows me to select the right language and technology to match the specific problem – not the other way around.
Technologies:
My primary backend framework is Nest.js, which I use to build microservice-based applications and asynchronous communication systems using message brokers (e.g., RabbitMQ). Depending on the needs, I also work with other communication patterns such as RPC or real-time connections via sockets.
When required, I develop serverless solutions, often based on AWS Lambda. I have experience working with both relational and non-relational databases, particularly MongoDB and Redis, as well as full-text search engines like Elasticsearch.
Technologies:
I have been exploring artificial intelligence and its applications in software development for some time now. I’m particularly interested in integrating AI models into backend systems and leveraging them to support and automate processes within applications. I experiment with tools like LangChain and Ollama, as well as approaches such as RAG and Agentic AI.
I also use AI tools daily for writing code, creating tests, and producing documentation. This speeds up my work and allows me to focus on other creative and high-value tasks.
Technologies:
In both my professional and personal projects, I aim to design solutions that are cloud-ready from the very beginning. I most frequently work with AWS, Docker, and the Infrastructure as Code approach using Terraform.
I regularly work with CI/CD pipelines, mainly using GitLab CI and GitHub Actions, and occasionally Jenkins. Currently, I’m expanding my knowledge of Kubernetes and advanced AWS services to create even more scalable and fault-tolerant systems.
Technologies: