Python Engineer with MLOps

🏢 Summary: The offer is for an ML Engineer focused on building and maintaining data pipelines and production-grade machine learning solutions in an Azure-based cloud environment. The role involves working with PySpark, Airflow, Kubernetes, and Infrastructure as Code to develop, deploy, and monitor scalable ML systems. You will contribute to forecasting and commodities projects, ensuring reliable data processing, CI/CD automation, and robust observability. 🗂️ Requirements: Strong experience in Python development for production systems, Hands-on experience with PySpark and distributed data processing, Experience with Airflow for workflow orchestration, Proficiency in Azure cloud services, Practical experience with Infrastructure as Code, Experience automating CI/CD pipelines using GitHub Actions, Experience with data quality monitoring and observability, Experience with Kubernetes and Docker, Ability to deploy and monitor ML models in production, Advanced English (B2/C1 level) 📃 Skills: Python, PySpark, Airflow, Spark, Azure, AzureML, Kubernetes, Docker, Terraform, GitHub, GitHubActions, AzureDevOps, pandas, scikit-learn, numpy, Grafana, Prometheus, Git 🏢 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 Forecasting & 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. Responsibilities – 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 1 engineer from VL, two from client side 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 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: Machine Learning Engineer role focused on deploying and maintaining production-ready ML pipelines and computer vision solutions on retail edge devices. The position involves building scalable cloud and edge architectures, automating ML workflows, and ensuring reliable deployment across thousands of devices using Azure and Python-based technologies. The role also includes collaboration with Data Scientists and contributing to AI-powered projects through monitoring, optimization, and technical consulting. 🗂️ Requirements: 5+ years of software engineering experience, Bachelor’s or Master’s degree in Computer Science or related field, Expert-level Python skills, Advanced Airflow experience, Advanced Docker experience, Advanced GitHub Actions experience, Strong Azure cloud expertise, Ability to work independently, English proficiency at B2/C1 level, Availability for hybrid work model 📃 Skills: Python, Azure, Docker, Airflow, GitHub, DeepStream, Streamlit, PostgreSQL, Terraform, ETL, CCTV 🏢 Description: VirtusLab is a leading European software consulting and engineering company. 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 professionals to make a substantial impact in the software industry. About the role Driving business innovation through production-ready machine learning pipelines. Collaboration focuses on deploying and maintaining ML workflows while leveraging Azure for cloud computing and on-prem clusters for ETLs. The scope of services involves close cooperation with Data Scientists, active contribution to AI-powered projects, and consulting on technical solutions and translating complex details for business stakeholders. Business delivery is achieved through the independent deployment and monitoring of models in production, combined with building and maintaining analytical dashboards for continuous insights. Furthermore, the engagement encompasses driving technical excellence across the project environment by fostering knowledge sharing and delivering high-level technical sessions. Python Expert Cloud (prefered Azure) Advanced Docker Advanced Airflow Advanced GitHub Actions Advanced English Advanced View available projects Project Computer Vision / Integration Project Scope The scope of services for the Machine Learning Engineer involves bridging the gap between data science and operational deployment at scale, focusing on the integration and automation of Machine Learning models directly onto retail edge devices, such as self-checkout tills. The core delivery includes: Development and maintenance of components for processing CCTV data, leveraging technologies like NVidia Deepstream. Streamlining the data onboarding process to enable the creation of specialized solutions by Data Science units. Designing and implementing scalable, high-quality code and architectures within cloud and edge environments. Optimization of data storage and processing in the cloud, selecting the most effective tools and architectures to meet business requirements. Enhancing the monitoring, reliability, and stability of deployed solutions, including the delivery of automated testing suites and simulation environments for edge devices. Fostering technical alignment with cross-functional units to ensure the seamless integration of ML models with retail tills, driving customer experience enhancement through innovative technologies. Tech Stack Python, Docker, DeepStream, Airflow, Azure, GitHub Actions, Streamlit, PostgreSQL, Terraform Project Challenges – Deploying and monitoring deployment to 10,000 devices – Ensuring similar behaviour on all devices at the same time – Dealing with internet interruptions during deployment – Dealing with the raw scale of data from thousands of cameras Project environment 3x Python Engineers, without an SDM, operating mostly in the larger Computer Vision team that, apart from engineers, consists of three Data Scientists, a Data Science Manager and Product Manager. The Engineering Team is distributed in Poland while the broader team is distributed in Poland and the United Kingdom. What we expect in general: Minimum 5 years of general software engineering experience with master’s or bachelor’s degree in Computer Science or related field Expert-level Python programming skills and extensive hands-on experience with Airflow, Docker, and GitHub Actions Strong Azure cloud expertise combined with ownership mindset and proven ability to work independently Good command of English (B2/C1). Availability to work in a hybrid model from time to time. 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 Access to the above perks is optional and completely voluntary for B2B contractors Apply now

🏢 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: Opportunity to drive business innovation by building and deploying production-ready machine learning pipelines in a hybrid cloud environment for a major UK retailer. The role focuses on end-to-end ML lifecycle implementation, Azure-based infrastructure provisioning, and developing scalable data pipelines and APIs for price optimisation solutions. You will collaborate closely with data scientists and engineers to productionise models and ensure robust monitoring and DevOps practices. 🗂️ Requirements: Strong experience in Python development, Hands-on experience with full Machine Learning Lifecycle implementation, Experience with Infrastructure as Code for cloud resource provisioning, Experience building data pipelines, preferably with PySpark, Knowledge of production system monitoring, Good English proficiency (B2/C1), Availability for hybrid work model 📃 Skills: Python, PySpark, Airflow, Azure, AzureML, Terraform, Spark, Kubernetes, FastAPI, MLflow, CI/CD, GitHub, Docker, Splunk 🏢 Description: VirtusLab is a leading European software consulting and engineering company. 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 professionals to make a substantial impact in the software industry. About the role Driving business innovation through production-ready machine learning pipelines. Collaboration focuses on deploying and maintaining ML workflows while leveraging Azure for cloud computing and on-prem clusters for ETLs. The scope of services involves close cooperation with Data Scientists, active contribution to AI-powered projects, and consulting on technical solutions and translating complex details for business stakeholders. Business delivery is achieved through the independent deployment and monitoring of models in production, combined with building and maintaining analytical dashboards for continuous insights. Furthermore, the engagement encompasses driving technical excellence across the project environment by fostering knowledge sharing and delivering high-level technical sessions. Project Scope Delivering price optimisation solutions in close cooperation with a major UK retailer’s data science team. The project aims to enable quick exploration and productionisation of the ML models and respective optimisation algorithms in a hybrid-cloud environment. The ultimate objective is providing APIs for the optimiser to solve pricing class problems across multiple business domains. The scope of cooperation covers: Implementing the end-to-end Machine Learning Lifecycle, starting from data preparation through automated deployment to continuous monitoring of data and models in production. Developing PySpark data pipelines to load and transform large amounts of data to produce significant features used in modelling and analytics. Provisioning all cloud resources supporting model development in AzureML with IaC using Terraform Selecting the best architectural patterns to solve business problems. Building robust and maintainable code in the cloud and on-prem to bring models fast and reliably to production Establishing a mature DevOps culture and developing solutions reusable in multiple business domains. Tech Stack Python (PySpark, Airflow, Azure SDK, fastapi, mlflow), Spark on K8S, Azure ML and IaC with Terraform, CI/CD with GitHub Actions, Docker, Splunk. Challenges Addressing numerous pricing problems in the global retailer world sharing similar structures and constraints. The focus is on building robust solutions reusable across multiple domains, leveraging a hybrid on-prem and cloud infrastructure, and ensuring top quality while maintaining quick iterations. Project Environment The project delivery involves a core engineering team of 5-7 professionals in Poland, collaborating closely with the client’s product management, data science team, and internal engineers. What we expect in general: Strong track record in writing high-quality Python code. Hands-on experience with implementing different stages of the Machine Learning Lifecycle. Experience with Infrastructure as Code to set up Cloud resources. Experience with creating data pipelines (ideally with PySpark). Solid understanding of the importance of monitoring in production systems. Good command of English (B2/C1). Availability to work in a hybrid model from time to time. 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 Access to the above perks is optional and completely voluntary for B2B contractors

🏢 Summary: Opportunity to productionize and scale an ML-driven data quality system (Anomalsky) on GCP, combining classic ML and LLM reasoning to detect and explain row-level data anomalies. The role focuses on building anomaly detection and clustering pipelines, integrating them into acquisition workflows, and developing a real-time validation layer. You will collaborate with data engineers and product teams to operationalize models and continuously improve data quality at scale. 🗂️ Requirements: Strong Python and production ML experience, Experience deploying ML models into production pipelines, Hands-on experience with unsupervised anomaly detection (kNN, Isolation Forest, autoencoders), Experience with clustering on large-scale tabular data, Experience combining classic ML with LLMs for reasoning and validation, Experience with Airflow and Spark (Dataproc), Experience with BigQuery and Snowflake, Experience with Iceberg and Trino/Starburst, Experience with GCP and Docker, Experience with Terraform and CI tools, Experience with MLflow, Professional English proficiency 📃 Skills: Python, Airflow, Spark, Dataproc, BigQuery, Snowflake, Iceberg, Trino, Starburst, AWS, GCP, Docker, Terraform, Jenkins, GitHub, Scikit-learn, MLflow, kNN, IsolationForest, Autoencoders, Clustering, LLM 🏢 Description: VirtusLab is a leading European software consulting and engineering company. 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 professionals to make a substantial impact in the software industry. About the role Productionizing and scaling an ML-driven data quality system across the organization. The scope of services involves: building and tuning anomaly-detection and clustering pipelines, pairing classic ML with LLM reasoning to flag and explain issues, collaborating with data producers to fix root causes, and creating as well as maintaining validator models that turn detected anomalies into better future data. Project Anomalsky Project Scope Our client is a NASDAQ-listed B2B data company powering Go-To-Market strategies with a 360-degree view of every customer, a view whose value depends on the quality of billions of person and company records. Anomalsky is the ML system built to catch what traditional observability misses: row-level semantic anomalies (e.g., a first_name, title, company_name). Three layers, an ML layer (embeddings + unsupervised clustering) flags suspicious records at scale, an LLM layer removes false positives and explains each cluster, and an optional human-in-the-loop lets domain experts resolve whole clusters at once. The MVP already drove ~40k crucial record corrections in production. What’s next: the MVP is landing on GCP now. Once it’s operational, the mission is to scale Anomalsky across the entire organization, embedding it into Acquisition pipelines and building a real-time variant that scans data before it reaches customers. The scope of cooperation covers Productionizing Anomalsky on GCP and scaling it to operational, organization-wide use. Evolving the ML / LLM / human-in-the-loop design and the feedback loop that turns expert reviews into reusable knowledge. Prototyping the low-latency real-time variant. Integrating Anomalsky into existing workflows, starting with Acquisition. Tech Stack Python, Airflow, BigQuery, Snowflake, Spark (Dataproc), Databricks, Iceberg, Starburst, Trino, AWS, GCP, Docker, Terraform, Jenkins, GitHub, Scikit Learn,  unsupervised anomaly detection (kNN, Isolation Forest, autoencoders), recursive clustering, classifiers on real + synthetic data, MLflow, LLM-based reasoning. Project environment ML and data engineers from VirtusLab collaborating with customer data engineers and product management. What we expect in general Strong Python and production ML skills, with a proven track record of shipping models into real production pipelines. Hands-on experience using classic ML to surface data quality issues at scale: unsupervised anomaly detection (kNN, Isolation Forest, autoencoders) and clustering on messy real-world tabular data. Practical experience pairing classic ML with LLMs: using models to flag suspicious records and LLMs for reasoning, false-positive filtering, and the final verification of anomalies. Solid data engineering background across the modern stack (Airflow, Spark/Dataproc, BigQuery, Snowflake, Iceberg/Trino) and the production toolchain (GCP, Docker, Terraform, CI, MLflow). Pragmatic, product-oriented approach focused on incremental value delivery and seamless integration into existing workflows. Professional fluency in English, enabling smooth technical and business discussions in an international environment. 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 Access to the above perks is optional and completely voluntary for B2B contractors

🏢 Summary: Founding engineer role in a greenfield, AI-driven initiative to build an intelligent internal platform that enhances developer experience across coding, debugging, testing, and deployment. The position focuses on designing and integrating LLM-powered agents and infrastructure within a large-scale engineering environment. You will collaborate in a globally distributed team to deliver AI tools embedded into everyday developer workflows. 🗂️ Requirements: Strong hands-on experience in Python, Proven experience integrating or building with LLMs, AI agents, or coding assistants, Ability to design and implement API integrations, Experience building distributed or backend systems, Ability to integrate systems with developer tools and services, Proficiency in English for technical collaboration across time zones, Polyglot programming skills and ability to learn new technologies quickly 📃 Skills: Python, TypeScript, Scala, Java, LLMs, OpenAI, Anthropic, APIs, AWS, GRPC, MySQL, GitHub, Slack, Docker, Kubernetes, CI/CD, GCP 🏢 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 a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains Strong, hands-on experience in Python Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS) Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) 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 And a lot more!

🏢 Summary: Join a founding team building an AI-powered internal platform to enhance developer experience across a large-scale engineering organization. The role focuses on designing and integrating LLM-based agents and infrastructure into everyday developer workflows. This greenfield project offers high impact through building intelligent tools that support coding, testing, debugging, and deployment. 🗂️ Requirements: Strong hands-on experience in Python, Practical experience integrating or building with LLMs, AI agents, or coding assistants, Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to collaborate with distributed international teams, Professional proficiency in English 📃 Skills: Python, TypeScript, Scala, Java, AWS, GRPC, MySQL, OpenAI, Anthropic, GitHub, Slack, Docker, Kubernetes, GCP, CI/CD 🏢 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 a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains Strong, hands-on experience in Python Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS) Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) 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 And a lot more!

🏢 Summary: Opportunity to join a newly formed, globally distributed team building an AI-powered internal developer platform for a large-scale engineering organization. The role focuses on designing and integrating LLM-based tools and agent systems that enhance coding, testing, and deployment workflows. You will help architect and implement core AI infrastructure and integrations within a greenfield, startup-like environment. 🗂️ Requirements: Hands-on experience integrating or building with LLMs, AI agents, or coding assistants, Strong experience in Scala or another modern JVM language (Kotlin or Java 17+), Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to collaborate in a distributed team across time zones, Professional English communication skills 📃 Skills: Python, TypeScript, Scala, Java, Kotlin, LLM, OpenAI, Anthropic, API, AWS, GRPC, MySQL, GitHub, Slack, Docker, Kubernetes, GCP, CI/CD 🏢 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 a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains. Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview. Strong, hands-on experience in at least one of the following: Scala, or another modern JVM language (e.g., Kotlin, Java 17+). A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment. Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone. Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows. Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS). Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) 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 And a lot more!

🏢 Summary: Founding engineer role in a greenfield, AI-driven internal platform aimed at revolutionizing developer experience at scale through LLM-powered tools and agent-based systems. The position focuses on designing and integrating AI capabilities into daily development workflows across a large, globally distributed organization. You will collaborate internationally to build core infrastructure and intelligent automation supporting coding, testing, and deployment processes. 🗂️ Requirements: Hands-on experience building or integrating LLMs, AI agents, or coding assistants, Strong experience in Scala or another modern JVM language, Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to build and maintain backend infrastructure, Fluent English for technical collaboration, Availability for collaboration with US West Coast time zone 📃 Skills: Python, TypeScript, Scala, Java, Kotlin, LLM, OpenAI, Anthropic, API, AWS, GRPC, MySQL, GitHub, Slack, Docker, Kubernetes, GCP, CI/CD 🏢 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 a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains. Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview. Strong, hands-on experience in at least one of the following: Scala, or another modern JVM language (e.g., Kotlin, Java 17+). A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment. Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone. Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows. Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS). Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) 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 And a lot more!