Software Developer in Test (Senior)

🏢 Summary: The offer is for a QA Engineer responsible for manual and automated testing of a multi-platform desktop application (ToolBox for JetBrains IDEs). The role focuses on ensuring quality before releases, building automated testing infrastructure, and collaborating with developers to improve reliability and user experience. The project supports large-scale management of developer tools and emphasizes strong engineering standards. 🗂️ Requirements: Java or Kotlin programming experience, Experience with JUnit, Ability to read and understand test and production code, Experience in building automated testing infrastructure and processes, Ability to identify critical and fragile areas for testing, Experience with manual testing, Ability to work independently and in a team, Ability to quickly learn new concepts 📃 Skills: Java, Kotlin, JUnit, Spring, React, Redux, PostgreSQL, S3, TeamCity, Space, CI, Automation, Testing 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role We are looking for a QA Engineer who will be responsible for the ToolBox for JetBrains IDEs (IntelliJ, PyCharm, etc.). The person will be responsible for both manual testing of the plugin before each release, but also for driving the automation of tests, either hands-on and/or by working with plugin developers. We need people who can work with users/partners to determine the most important paths as well as identify the parts in the tool that are fragile and focus on those. The Toolbox centralizes the management of all your JetBrains IDEs and development tools, completely reimagining how developers discover, install, and update their software Project scope The project builds a multi-platform desktop application that helps large organizations manage developer tools such as IDEs and plugins. It focuses on delivering a seamless user experience, enabling version control and configuration management at scale. Tech stack Kotlin, Spring, React, Redux, PostgreSQL, S3, TeamCity (for CI), Space (for code reviews) Your future team The team consists of 4 engineers on our side and over 5 on the client side, collaborating closely through code reviews. They bring strong experience in developer tooling and maintain high engineering standards across a distributed setup. What we expect in general Java or Kotlin programming experience. Having JUnit experience is preferrable. The ability to understand other people’s code (both test and product code). The ability to grasp new concepts quickly and to work both in a team and independently. Experience in building automated testing infrastructure and processes. Experience in performance testing will be a plus. Willingness to propose new ideas and improvements for current approaches. A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Engineering role focused on building a desktop platform for managing and deploying local AI inference, using Kotlin and Compose Desktop. The position involves designing and implementing developer tooling such as IDE plugins and agent integrations, with full ownership over architecture, testing, and delivery. Work centers on creating extensible tooling for local LLM lifecycle management and agent connectivity. 🗂️ Requirements: Strong Kotlin or Java expertise, Experience with asynchronous and concurrent programming, Practical knowledge of Kotlin Coroutines, Experience building desktop applications, Ability to design and implement REST API integrations, Experience with configuration formats (toml, json, yaml), Knowledge of model lifecycle management, Experience with native OS packaging (msi, deb, dmg), Fluent English 📃 Skills: Kotlin, Java, Kotlinx.coroutines, Compose, Jetpack, REST, TOML, JSON, YAML, LLM, IntelliJ, Multiplatform, MSI, DEB, DMG, Swing, SWT 🏢 Description: VirtusLab is a leading European software consulting and engineering company, home to over 350 EU-based professionals. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role We are looking for engineers interested in building various tooling using mainly Kotlin. Our team is working on IntelliJ plugin, IDEs, coding agents or frameworks for Local AI inference. Your job will be focused 100% on technology and your users will be developers. You will work withing, small, flexible team and you will have a lot of authonomy: you will be responsible for design, scope, testing and implementation. You will work with tooling engineers, and you will be part of an organisation specialized in developer tooling. Kotlin/Java Expert Kotlinx.coroutines / concurrent programming Advanced Compose Desktop (Jetpack Compose) Nice to have Kotlin multiplatform Nice to have Build tools/IDE development Nice to have English Advanced Project Local Inference Platform Project Scope We are building a desktop application for deploying and configuring local inference on local devices (e.g. NVIDIA Spark / DGX Spark), managing model lifecycle (start/stop), and connecting coding agents like Claude Code and Codex to locally hosted models. Currently an internal MVP, on the road to open source. Tech Stack Kotlin, Compose Desktop (with JetPack Compose roots), kotlinx.coroutines, REST APIs for model deployment management Agent layer: configuration files in toml/json/yaml, LLM proxy routing from agents to BE Packaging: native installers — msi (Windows), deb (Linux), dmg (macOS) Challenges Building a desktop control plane for local AI agents that abstracts away the messy parts of running LLMs on heterogeneous hardware — model lifecycle, proxy routing, agent configuration, and OS-specific quirks (path separators, signing, packaging) — while keeping the system extensible enough to evolve toward open source. Visualising model statistics and system load on top of a backend that actually does the deployment. Team Small, startup-like team on the JetBrains side — no bureaucracy, direct contact with potential users, fast iteration. Code reviews as part of the process. What we expect in general Strong Kotlin skills or Strong Java expertise with knowledge of Kotlin Understanding of asynchronous and concurrent programming, at best with Kotlin Coroutines High agency and ability to drive work in a changing environment Engineering pragmatism: cutting complexity while keeping the system extensible Hands-on experience using LLMs daily, with the judgment to know when they help and when they don’t Fluency in English, with good communication skills for a remote-first team Self-motivation and the ability to take full ownership of features end-to-end Nice to have Experience with different LLM agents and their configurations Experience with IDE development, especially around JetBrains IDEs Hands-on experience with developer tooling (compiler, build tools, linters, IDE, agents) Experience with creating OS-native, desktop applications Experience with creating GUIs using JVM (Swing, SWT, etc.) A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Engineering role focused on building a cross-platform desktop application for managing and deploying local AI inference models, using Kotlin and Compose Desktop. The position involves creating UI, integrating with REST APIs, configuring AI agents, and handling packaging for Windows, macOS, and Linux. It offers the opportunity to shape an early-stage developer tool evolving toward open source. 🗂️ Requirements: Strong Kotlin proficiency, Experience with Compose Desktop, Knowledge of asynchronous and concurrent programming with Coroutines, Experience integrating with REST APIs, Understanding of cross-platform desktop development differences, Ability to manage and parse TOML/JSON/YAML configuration files, Experience building or packaging desktop applications for Windows, macOS, and Linux, Understanding of LLM workflows and local model deployment 📃 Skills: Kotlin, Compose, Coroutines, REST, TOML, JSON, YAML, LLM, MSI, DEB, DMG, mitmproxy, LiteLLM, OpenRouter 🏢 Description: VirtusLab is a leading European software consulting and engineering company, home to over 350 EU-based professionals. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role We’re looking for an engineer to join a small, startup-like team building a desktop tool for local AI inference. You’ll work with Kotlin and Compose Desktop to create an application that deploys, configures and manages AI models running on local devices – think NVIDIA Spark, Claude Code, and Codex connected to locally hosted models. Your daily work will include building the UI in Compose Desktop, integrating with backend REST APIs for model deployment, and setting up agent configurations through TOML/JSON/YAML files. You’ll also work on LLM proxy routing and create installers for Windows, macOS and Linux. The team already has an internal MVP and talks directly with potential users. We’re on the road to making it open source. If you want to shape a developer tool from the early stages, this is it. Project Local Inference Platform Project Scope We are building a desktop application for deploying and configuring local inference on local devices (e.g. NVIDIA Spark / DGX Spark), managing model lifecycle (start/stop), and connecting coding agents like Claude Code and Codex to locally hosted models. Currently an internal MVP, on the road to open source. Tech Stack Kotlin, Compose Desktop (with JetPack Compose roots), kotlinx.coroutines Backend integration: REST APIs for model deployment management Agent layer: configuration files in toml/json/yaml, LLM proxy routing from agents to BE Packaging: native installers — msi (Windows), deb (Linux), dmg (macOS) Nice-to-have tooling: mitmproxy for HTTP debugging, LiteLLM/OpenRouter-style proxy layers. Challenges Building a desktop control plane for local AI agents that abstracts away the messy parts of running LLMs on heterogeneous hardware — model lifecycle, proxy routing, agent configuration, and OS-specific quirks (path separators, signing, packaging) — while keeping the system extensible enough to evolve toward open source. Visualising model statistics and system load on top of a backend that actually does the deployment. Team Small, startup-like team on the JetBrains side — no bureaucracy, direct contact with potential users, fast iteration. Code reviews as part of the process. What we expect in general Strong Kotlin skills and genuine interest in Compose Desktop as a UI framework Understanding of asynchronous and concurrent programming with Kotlin Coroutines Awareness of cross-platform differences (file paths, OS-specific packaging) Engineering pragmatism: cutting complexity while keeping the system extensible System-level thinking: understanding how UI, backend APIs, agent configs and proxy layers fit together Hands-on experience using LLMs daily, with the judgement to know when they help and when they don’t Fluency in English, with good communication skills for a remote-first team Self-motivation and the ability to take full ownership of features end-to-end Experience with different LLM agents and their configurations (nice to have) Experience with mitmproxy or similar HTTP traffic inspection tools (nice to have) Experience with LLM proxy layers such as LiteLLM or Openrouter (nice to have) Experience creating and signing OS installers (MSI, DEB, DMG – nice to have) A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Backend Python Engineer role focused on building a desktop control plane for deploying and configuring local AI inference on devices like NVIDIA Spark. The position involves managing model lifecycle, integrating coding agents with locally hosted models, and evolving an internal MVP toward an open-source developer tool. Work includes backend development, LLM proxy routing, Docker lifecycle management, and production-grade API design. 🗂️ Requirements: Strong Python skills, Experience with FastAPI or Flask, Knowledge of asynchronous and concurrent programming, Experience with backend API development, Understanding of Docker lifecycle management, Experience integrating external APIs, Knowledge of LLM proxy routing concepts, Ability to design idempotent endpoints and implement retry mechanisms, Experience with relational databases, Fluent English 📃 Skills: Python, FastAPI, Flask, Asyncio, LiteLLM, Pydantic, PostgreSQL, AWS, Docker, HuggingFace, CUDA, vLLM, Ollama, LLM, API 🏢 Description: VirtusLab is a leading European software consulting and engineering company, home to over 350 EU-based professionals. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role We’re looking for an engineer to join a small, startup-like team building a tool for deploying and configuring local AI inference on local devices like NVIDIA Spark. You’ll work on managing the model lifecycle (start/stop) and connecting coding agents—such as Claude Code, Codex, and others—to locally hosted models. Your daily work will be on the backend: adapting LiteLLM configuration as agent APIs (Claude Code, Codex, etc.) evolve, managing the lifecycle of docker images that ship the agents, integrating with the Hugging Face API for model downloads, and getting the production essentials right—idempotent endpoints, retries with backoff, and straightforward migrations. The team already has an internal MVP and talks directly with potential users. We’re on the road to making it open source. If you want to shape a developer tool from the early stages, this is it. Project Local Inference Platform for Python Engineers Project Scope A desktop application for deploying and configuring local AI inference on local devices (e.g., NVIDIA Spark / DGX Spark), managing model lifecycle (start/stop), and connecting coding agents like Claude Code and Codex to locally hosted models. Currently an internal MVP, on the road to open source. Tech Stack Python, Asyncio, FastAPI, LiteLLM, Pydantic, PostgreSQL, AWS, Agent layer: LLM proxy routing from agents to BE Challenges Building a desktop control plane for local AI agents that abstracts away the messy parts of running LLMs on heterogeneous hardware — model lifecycle, proxy routing, agent configuration, and OS-specific quirks (path separators, signing, packaging) — while keeping the system extensible enough to evolve toward open source. Visualising model statistics and system load on top of a backend that actually does the deployment. Team Small, startup-like team on the JetBrains side — no bureaucracy, direct contact with potential users, fast iteration. Code reviews as part of the process. What we expect in general: Strong Python skills with experience in backend frameworks such as FastAPI or Flask. Solid understanding of concurrent and asynchronous programming. Ability to rapidly prototype and iterate on emerging ideas. Engineering pragmatism: cutting complexity while keeping the system extensible. System-level thinking: understanding how the Docker lifecycle, LLM proxy routing, model management, and the agent layer fit together. Hands-on experience using LLMs daily, with the judgment to know when they help and when they don’t. Self-motivation and the ability to take full ownership of features end-to-end. Fluency in English, with good communication skills for a remote-first team. Nice to have: Experience using Docker for local deployment and service orchestration. Experience setting up and maintaining an LLM proxy layer such as LiteLLM or OpenRouter. Experience with vLLM or ollama. Familiarity with the HuggingFace API and model distribution patterns. Experience with local GPU inference setups (CUDA, NVIDIA hardware) Background working with coding agents (Claude Code, Codex, Aider) and their configurations. Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The role focuses on building and owning robust data pipelines on a Spark cluster orchestrated with Airflow, while ensuring high data quality, observability, and reliable ML model deployment. You will work with Azure infrastructure using Infrastructure as Code and automate CI/CD workflows to support production-grade ML solutions. The position bridges data engineering and MLOps to deliver scalable, trustworthy systems in a retail loss prevention project. 🗂️ Requirements: Expert-level Python development, Strong experience with PySpark and large-scale data processing, Hands-on experience with Airflow for workflow orchestration, Experience provisioning cloud infrastructure using Infrastructure as Code, Proficiency with Azure or equivalent cloud platforms, Experience building and maintaining CI/CD pipelines with GitHub Actions, Experience with data quality validation and monitoring, Experience with observability and monitoring tools, Ability to productionize and monitor ML models, Advanced English (B2/C1) 📃 Skills: Python, PySpark, Airflow, Azure, Terraform, GitHub, Actions, CI/CD, Spark, Kubernetes, Grafana, Prometheus, MLOps 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Python Expert Cloud (prefered Azure) Advanced IaC Regular GitHub Actions Regular Pyspark Regular Airflow Regular Experience with observability Nice to have MLOps: Proven ability to productionize models and set up monitoring Nice to have Dashboarding / visualization skills Nice to have Kubernetes Nice to have English Advanced Project Loss Prevention Project Scope Loss prevention in retail involves the strategic implementation of processes and technologies designed to identify, mitigate, and prevent the disappearance of inventory. To achieve that an Engineering and a Data Science team within a major UK retailer partner to bridge the gap between experimental ML models and robust, production-grade systems. By embedding engineering excellence into the data science lifecycle, the team ensures that loss prevention insights are delivered with high reliability. In this project you will not only develop high-quality Python code, but also implement trustworthy data pipelines on a big Spark cluster orchestrated with Airflow, setup highly automated CI/CD pipelines with Github Actions, and provision Azure infrastructure as code with Terraform. Tech Stack Python, PySpark, Airflow Azure, IaC (Terraform), CI/CD (Github Actions), Observability (Grafana/Promotheus), MLOps, Kubernetes Challenges Establish a resilient MLOps Ecosystem by integrating robust observability, experiment tracking and automated deployment to model serving infrastructure. Improve the reliability and observability of data pipelines to guarantee trust-worthy data. Advancing DevOps Maturity through the implementation of standardized pipelines, enabling rapid iteration and minimizing manual intervention. Team 3 Engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. Good command of English (B2/C1 level), comfortable utilizing the language daily. A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The role focuses on building and owning reliable data pipelines and MLOps infrastructure for a retail loss prevention project using Spark, Airflow, and Azure. You will develop production-grade Python solutions, automate CI/CD processes, and provision cloud infrastructure as code while enhancing monitoring and observability. The position bridges data science and engineering to deliver robust, scalable ML systems in production. 🗂️ Requirements: Strong experience with Python in production environments, Hands-on experience with PySpark and Spark clusters, Experience with workflow orchestration using Airflow, Experience with Azure or equivalent cloud platforms, Practical experience with Infrastructure as Code, Experience automating CI/CD pipelines with GitHub Actions, Knowledge of data validation and monitoring practices, Experience with Kubernetes in production, Experience with observability and monitoring tools, Upper-intermediate English (B2/C1) 📃 Skills: Python, PySpark, Spark, Airflow, Azure, Terraform, GitHub, CI/CD, Kubernetes, Grafana, Prometheus, MLOps 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Project: Loss Prevention Project Scope Loss prevention in retail involves the strategic implementation of processes and technologies designed to identify, mitigate, and prevent the disappearance of inventory. To achieve that an Engineering and a Data Science team within a major UK retailer partner to bridge the gap between experimental ML models and robust, production-grade systems. By embedding engineering excellence into the data science lifecycle, the team ensures that loss prevention insights are delivered with high reliability. In this project you will not only develop high-quality Python code, but also implement trustworthy data pipelines on a big Spark cluster orchestrated with Airflow, setup highly automated CI/CD pipelines with Github Actions, and provision Azure infrastructure as code with Terraform. Tech Stack Python, PySpark, Airflow Azure, IaC (Terraform), CI/CD (Github Actions), Observability (Grafana/Promotheus), MLOps, Kubernetes Challenges Establish a resilient MLOps Ecosystem by integrating robust observability, experiment tracking and automated deployment to model serving infrastructure. Improve the reliability and observability of data pipelines to guarantee trust-worthy data. Advancing DevOps Maturity through the implementation of standardized pipelines, enabling rapid iteration and minimizing manual intervention. Team 3 Engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. Good command of English (B2/C1 level), comfortable utilizing the language daily. A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Senior Infrastructure Engineer role focused on maintaining, scaling, and optimizing large-scale on-premise developer infrastructure for a major investment bank, supporting over 10,000 users. The position involves ownership of core developer tools, automation, performance troubleshooting, and integration of LLM-based tooling in a secure enterprise environment. 🗂️ Requirements: 5+ years commercial experience in system administration or infrastructure engineering, Strong Linux administration expertise, Deep understanding of networking concepts, Hands-on experience with Jenkins, Bitbucket, and BuildBarn, Proficiency in Bash and Python scripting, Ability to troubleshoot and resolve large-scale performance issues, Experience supporting on-premise infrastructure, Ability to work across Linux, Windows, and macOS environments, Experience in large-scale Enterprise or financial environments, English proficiency at B2/C1 level 📃 Skills: Linux, Windows, macOS, Networking, Jenkins, Bitbucket, BuildBarn, Bash, Python, PowerShell, Git, AWS, Azure, JVM, C++, Bazel, MCP, AI-agents, Claude, Copilot, Citrix, JIRA 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role You will join our team to maintain, scale, and optimise our core on-premise infrastructure for a major investment bank. Your main goal will be to take ownership of essential developer tools and services including Jenkins, Bitbucket, and BuildBarn ensuring their highest reliability for on-prem installations for a user base of over 10,000 developers. We rely on strong system administration skills, deep networking knowledge, and automation to keep our environments running smoothly. While 99% of our infrastructure is Linux-based, our team supports systems across Linux, Windows, and macOS ecosystems. If you join us as a Senior Engineer, you will also lead the diagnosis and resolution of complex performance bottlenecks across this large-scale infrastructure. Project scope We are working with the core developer tooling team responsible for 30k+ developers in one for the biggest investment bank. Our team is especially focused on LLM-based tools for developers – evaluation, trials, onboarding and customisation. After the phase of initial tests, the team now faces a need to onboard 1000s of new developers each week to use AI tooling. The team works closely with vendors and in-house teams to ensure that tools like Claude Code or Copilot CLI bring as much value as possible to the client developers. The team will work on automations, setup, MCPs and more.The team supports users – mainly via running trials and checks and helping with escalations from existing, hands-on support teams Tech stack Python, MCP, AI-agents, scripting, git, AWS, Azure, JVM, C++, Bazel Tools and Workflow Claude Code, Amp, Intellij, git, Kanban, Windows via Citrix, JIRA, BitBucket Challenges Customising LLM tools to fit the client’s environment and flows. Working on integration of existing and new context sources including various MCP. Tracking user’s needs and building a generic mechanism that fits multiple teams. The team will need to balance security requirements with pragmatism and users’ experience Team 4 people in the VL team working with bigger teams on the client’s side – distributed across Americas, Europe and Asia What we expect in general Solid background in Linux administration and a deep understanding of networking concepts. Hands-on experience in managing and optimising on-premise developer tools (such as Jenkins, Bitbucket, and BuildBarn). Proficiency in scripting languages (Bash and Python; basic knowledge of PowerShell is an asset) to automate administrative tasks. Strong analytical skills to diagnose, troubleshoot, and solve system performance problems at scale. Readiness to support a multi-platform environment (primarily Linux, with secondary support for Windows and macOS). Commercial experience working within large-scale Enterprise or financial environments is highly preferred. At least 5 years of commercial experience in system administration or infrastructure engineering. English skills at a [B2/C1] level, allowing for seamless communication. A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Entry-level QA Engineer role focused on learning and applying software testing fundamentals across web and mobile applications, with hands-on exposure to test automation and programming. The position offers mentorship and practical experience in manual and automated testing within an Agile environment. Ideal for recent graduates or students eager to build a strong foundation in QA and software development. 🗂️ Requirements: Basic knowledge of software testing principles (ISTQB Foundation or equivalent), Willingness to learn manual and automated testing, Basic Python skills, Understanding of web and mobile application testing basics, Ability to communicate in English (written and spoken), Ability to work in a team environment 📃 Skills: Python, Playwright, Selenium, Postman, Git, PHP, Symfony, Laravel, JavaScript, TypeScript, Go, PHPUnit, Codeception, Flutter, Dart, MySQL, MariaDB, UNIX, Kubernetes, RabbitMQ, Docker, GitLab, CodeMagic, Claude, Cursor, Gemini, Jira, Confluence, Slack, Sentry 🏢 Description: About the Role We are seeking a Junior QA Engineer who is eager to start a career in software testing and grow within our team.  You’ll help ensure the quality and reliability of our products used by thousands of users. This role is designed for someone at the beginning of their QA journey - you don’t need years of experience, just curiosity, motivation, and willingness to learn. You’ll be introduced to the fundamentals of software testing, learn how to work with web and mobile applications, and get hands-on practice with test automation and programming. Our team will provide mentorship, training, and guidance so you can build strong foundations in QA and software development. If you’re at the end years of your studies or freshly graduated and enthusiastic about technology, want to learn how modern software is built and tested, and are excited to grow your skills step by step, we’d love to meet you. Requirements Must have Basic knowledge of software testing principles (ISTQB Foundation Level or equivalent knowledge - certificate not required). Willingness to learn and develop skills in both manual and automated testing. High level of ownership and proactive mindset. Basic Python skills, enabling you to write simple functions or scripts. Curiosity, attention to detail, and motivation to grow in QA. Ability to work in a team and communicate clearly in English (written and spoken). Nice to Have Practical experience with AI tools (Claude Code, Junie etc.). First experience with test automation tools (e.g., Playwright, Selenium, or similar). Basic knowledge of API testing (e.g., using Postman). Familiarity with version control systems (Git). Understanding of Agile/Scrum basics. Interest in AI/ML and how it can support testing. Our Tech & QA Stack Languages/Frameworks: PHP 8+/Symfony 6+/Laravel 9+, JS/TypeScript, Go, PHPUnit, Codeception, Flutter/Dart Databases: MySQL, MariaDB Infrastructure: UNIX, Kubernetes, RabbitMQ Testing: Playwright, Python, Dart, Postman CI/CD: GitLab CI, Code Magic Containerization: Docker AI Tools: Claude Code, Jetbrains AI, Cursor, Gemini for Google Workspace Tools: Jira, Requirements & Test Management for Jira, Confluence, Slack, IDE (freedom of choice),  G Suite, Sentry Engineering Culture Agile Scrum + XP elements OOP, TDD, DDD, SOLID, Clean Code Code reviews, pull requests, automation mindset QA as part of cross-functional team Benefits and Perks Private healthcare Cafeteria system Training budget €800 per year Integration meetings (internal training, hackathon, integration trips and meetings) Referral Bonus Startup atmosphere Flexible hours Flexible working format - remote or hybrid Modern office, Chillout zone, Standing desk, parking for bicycles, and a cloakroom with showers Regular office lunches and integration meetings Some international travels included

🏢 Summary: The offer is for a Bazel-focused Developer Advocate combining consulting, development, and community engagement. The role involves leading Bazel migrations, building open source and internal tooling, and supporting pre-sales and training activities. It blends hands-on engineering with technical advocacy around build systems and SDLC practices. 🗂️ Requirements: 3+ years experience in backend, DevOps, or platform engineering, Experience with build tools and CI/CD systems, Practical experience with Bazel or another build tool, Strong knowledge of at least one ecosystem (JVM, C++, Rust, Go, NPM), Experience in developing and maintaining SDLC processes, Ability to work with C++ codebases, Experience in technical mentoring or training 📃 Skills: Bazel, Starlark, C++, CI/CD, JVM, Rust, Go, NPM 🏢 Description: VirtusLab is a leading European software consulting and engineering company, home to over 350 EU-based professionals. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role Project scope This role is focused on a mixture of consult and dev-rel work around Bazel. This means a mix of:– doing Bazel migration– promoting Bazel and our expertise through conferences, meetups, blog posts, and Social Media– developing open source and internal solutions focused on Bazel– pre-sales and consultancy work– training and mentoring developers on Bazel This role usually is connected with part-time work within other projects related to Bazel. Tech stack Bazel, Starlark, C++ Challenges This position requires exceptional skills in multitasking. It requires a willingness to public speaking, write articles, and activity within Social Media or discussion forums (e.g., Bazel Slack). It requires a lot of initiative and creativity. Team 2 developer advocate/experts. What we expect in general 3+ years of experience in backend, devops, or platform engineering Some experience in developing solutions around building tools, maintaining CI/CD, and other aspects of SDLC Some experience of Bazel or at least one other build tool. Candidate should know well at least one ecosystem (JVM, C++, Rust, GoLang, NPM etc.) Communication skills and a pragmatic approach to problem-solving Ability to work as a part of a team Pro-active approach to problem-solving, without hesitation in reaching out for help Being self-driven and self-managing tasks A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The offer is for an ML Engineer role focused on building and maintaining production-ready machine learning pipelines in an Azure-based cloud environment. The position involves deploying models, developing ML frameworks, and supporting forecasting and commodities projects using distributed data processing and DevOps practices. The role combines hands-on engineering with collaboration to standardize and scale AI solutions. 🗂️ Requirements: Strong experience in Python and production-level deployments, Experience with Azure cloud services, Experience with PySpark or other Spark-based distributed processing, Experience with Airflow or similar orchestration tools, Experience with Kubernetes ecosystem, Experience with Docker, Experience with Infrastructure as Code, Experience with CI/CD pipelines, Knowledge of MLOps and model monitoring, Experience with Git version control, Advanced English (B2/C1) 📃 Skills: Python, Azure, AzureML, PySpark, Spark, Airflow, Kubernetes, Docker, Terraform, Git, GitHub, GitHubActions, AzureDevOps, pandas, scikit-learn, numpy, MLOps, CI/CD, IaC 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role Join our team to drive business innovation with production-ready machine learning pipelines. You will play a key role in deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs. Collaborating closely with Data Scientists, you will contribute to AI-powered projects while shaping the organization’s technical culture. Python Advanced Cloud (prefered Azure) Advanced IaC Regular GitHub Actions Advanced Pyspark Regular Airflow Regular Experience with observability Nice to have MLOps: Proven ability to productionize models and set up monitoring Nice to have Productionize models and set up monitoring Regular Kubernetes Nice to have English Advanced View available projects Project Forecasting and Commodities Project Scope As an ML Engineer in Forecasting and Commodities, you will be involved in projects that support critical decision making processes, by applying your Python, PySpark, Kubernetes and Cloud (Azure) skills. You will be working in a technically mature ecosystem, implementing new features and covering new use-cases. Part of your responsibilities will be design and implementation of a data science innovation framework, as well making contributions to an overall engineering best practises of the organization. Your key responsibilities would be: Developing libraries, tools, and frameworks that standardise and accelerate development and deployment of machine learning models. Working in an Azure cloud environment, developing model training code in AzureML. Building and maintaining cloud infrastructure with IaC (infrastructure as code). Working with distributed data processing tools such as Spark, to parallelise computation for Machine Learning. Diagnosing and resolving technical issues, ensuring availability of high-quality solutions that can be adapted and reused. Collaborating closely with different engineering and data science teams, providing advice and technical guidance to streamline daily work. Championing best practices in code quality, security, and scalability by leading by example. Taking your own, informed decisions moving a business forward. Tech Stack Python, PySpark, Airflow, Docker, Kubernetes, Azure (incl. Azure ML), pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git, GitHub. Project Challenges Building a system that provides accurate and up-to-date business forecasts, by providing a set of tools that can be easily leveraged by data scientists and analysts. Streamlining the process of onboarding, deployment and patching new ML pipelines. Collaborating with cross-functional teams enhancing customer experiences through innovative technologies. Employing DevOps practises for reproducible patterns in multiple business domains. Team 3 engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Experience with orchestration tools such as Airflow. Knowledge of Spark or other distributed data processing tools. Experience with Kubernetes ecosystem as a user. Strong experience in Cloud (preferred Azure) and Docker Ability to work in a team and participate in the design process. Strong communicator. Team player with mentoring ability. Proactive and responsible Strategic thinker with big-picture perspective Good command of English (B2/C1). A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!