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Schedule Interview NowWorking at Softaims has been an experience that continues to shape my perspective on what it means to build quality software. I’ve learned that technology alone doesn’t solve problems—understanding people, processes, and context is what truly drives innovation. Every project begins with a question: what value are we creating, and how can we make it lasting? This mindset has helped me develop systems that are both adaptable and reliable, designed to evolve as business needs change. I take a thoughtful approach to problem-solving. Instead of rushing toward quick fixes, I prioritize clarity, sustainability, and collaboration. Every decision in development carries long-term implications, and I strive to make those decisions with care and intention. This philosophy allows me to contribute to projects that are not only functional, but also aligned with the values and goals of the people who use them. Softaims has also given me the opportunity to work with diverse teams and clients, exposing me to different perspectives and problem domains. I’ve come to appreciate the balance between technical excellence and human-centered design. What drives me most is seeing our solutions empower businesses and individuals to operate more efficiently, make better decisions, and achieve meaningful outcomes. Every challenge here is a chance to learn something new—about technology, teamwork, or the way people interact with digital systems. As I continue to grow with Softaims, my focus remains on delivering solutions that are innovative, responsible, and enduring.
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Development of scalable and reliable game data processing driven by Firebase Realtime Database, Managed Google Cloud SQL and Cloud Functions with Node JS, backend dashboard development with React/Typescript driven by Firebase Hosting/Auth.
Wrote a Telegram bot for a chat with ChatGPT. Here are some bot features: - keeping conversation context (aka remembering previous messages) - password authenticated users with the managed roles and access rights - service commands directly from the chat, e.g. resetting current conversation, adjusting the system role, changing current model etc - extendable software architecture to support multiple chat bots (e.g. Mattermost, Discord etc.) as well as the chat backends (e.g. Bard) - managed secrets with Transcrypt
For one of the largest German automotive company I have created a practical case study for deploying monitoring tools in Kubernetes for machine learning models. The aim of the project was to research ways of representing performance of a ML model with standard monitoring tools like InfluxDB/Grafana or Prometheus/Grafana. I've created 2 cases: transferring of inputs to the model and performance metrics to monitoring tools with Kafka or exposing Prometheus API directly from the model. For the first case I've created following Kubernetes setup: - Model Deployment with Seldon with REST API - Model Detector in Seldon with REST API - Kafka with the stream of outputs from the Model Detector - Telegraf to convert outputs to the metrics format and write them to InfluxDB - InfluxDB as metrics storage - Grafana Dashboard with InfluxDB as the data source For the second case following setup was created: - Combined Model and Detector Deployment with Seldon API and custom Prometheus endpoint for metrics - Prometheus service - Scraping configuration with corresponding Network Policies - Grafana with the Prometheus as the data source The case study proved possibility to deliver machine learning metrics to standard monitoring tools in Kubernetes environment.
For one of the largest German automotive company I was requested to develop a cross platform Desktop application for internal usage. It's main goal was to manage auth policies for cars, devices and users for third party service providers, manufacturers and other departments. I developed the application in Golang as a Chrome based web application with internal Go server and Bootstrap 5 driven interface. The main functionality included: - loading external policy validation rules as yaml files - client/server-side validation with error highlighting for the corresponding fields or field groups - multi-step expandable forms - server side rendering with Go-templates, Bootstrap 5 and vanilla JS - file manager to upload/download files - auth with PKI cards (certstore and smimesign library) - go-git integration and communication with the gitlab server to push and pull policy updates - signing commits with PKI - update system and protected delivery of binary artefacts to the customers from Azure pipelines
The goal of the project was to develop energy price calculation tool for a big energy provider company where all price components where delivered as a huge (over 2GB) pile of CSV files with tariffs data for all possible areas/subnets/consumption ranges/client types. The task was: - analyse and parse price components data - apply efficient search algorithms (binary search by multiple criteria) to for lookups - define GRPC photos to represent price models and price components - design API to receive calculation requests and response with calculation results - implement Go code with the calculation logic - build application code as docker images - deploy price generation tool in Azure Kubernetes - unittest all calculation steps - effort coordination with the frontend developers