AI Lead DevOps Engineer

🏢 Summary: Remote AI Lead Data Engineer role responsible for designing and delivering enterprise-grade AI data platforms while leading a team of engineers. The position focuses on building scalable Lakehouse architectures, advanced MLOps frameworks, and LLM orchestration pipelines. It bridges Data Science and Data Engineering to ensure robust, governed, and production-ready AI infrastructure. 🗂️ Requirements: 8–10 years of Data Engineering experience, Minimum 3 years in technical lead role, Expert-level Python, Expert-level SQL, Expert-level PySpark in distributed environments, Experience with SageMaker, Azure ML, or Vertex AI, Hands-on MLflow or Kubeflow for CI/CD, Experience with Monte Carlo or Datadog, Experience with Collibra or Alation, Implementation of Responsible AI guardrails, Knowledge of Medallion, Data Mesh, Lakehouse architectures, Experience with PII masking and data lineage, Knowledge of HIPAA and GDPR compliance 📃 Skills: Python, SQL, PySpark, SageMaker, AzureML, VertexAI, MLflow, Kubeflow, MonteCarlo, Datadog, Collibra, Alation, Lakehouse, Medallion, DataMesh, CI/CD, LLM, HIPAA, GDPR 🏢 Description: This is a remote position. The AI Lead Data Engineer acts as the technical lighthouse for our data squads. With 8–10 years of experience, you are responsible for the technical design and delivery of robust AI data platforms. You will bridge the gap between Data Science and Data Engineering, ensuring that our infrastructure supports advanced MLOps and LLM requirements while leading a team of engineers to maintain elite coding and governance standards. Key Responsibilities: Technical Leadership: Lead a squad of data engineers in the design and execution of end-to-end AI data architectures. AI Observability & Governance: Build frameworks for bias detection, ethical AI considerations, and auditability using platforms like Collibra or Alation. Infrastructure Design: Lead the transition to Data Lakehouse architectures and implement feature stores for enterprise-wide model reuse. Delivery Management: Work with stakeholders to manage project milestones, technical risks, and on-time delivery. Advanced MLOps: Implement enterprise-grade CI/CD for ML workflows using MLflow or Kubeflow. GenAI Orchestration: Design specialized pipelines for LLM evaluation frameworks and prompt-tuning datasets. Requirements 8–10 years of experience with at least 3 years in a lead role managing technical delivery. Expert-level Python, SQL, and PySpark optimization for distributed environments. Deep experience with AI platform services such as Amazon SageMaker, Azure ML, or Vertex AI. Hands-on experience implementing enterprise observability with Monte Carlo or Datadog. Experience with data governance platforms (Collibra/Alation) and implementing Responsible AI guardrails. Deep understanding of modern data patterns (Medallion architecture, Data Mesh, Lakehouse). Advanced knowledge of security frameworks, including PII masking, data lineage, and HIPAA/GDPR compliance. Exceptional ability to mentor junior engineers and communicate complex data strategies to business stakeholders. Benefits Professional training programs Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row

🏢 Summary: The offer is for an MLOps / AI Engineer to design, implement and maintain AI/ML solutions for banking and financial sector projects. The role focuses on building MLOps environments, automating training and deployment processes, and managing cloud-based AI infrastructure in production. You will support the full lifecycle of ML models, including monitoring and optimization in production environments. 🗂️ Requirements: 3–4 years of experience as MLOps Engineer, AI Engineer, Machine Learning Engineer or similar, Strong knowledge of Python, Experience building and maintaining ML solutions in production environments, Experience with Docker and containerization, Experience with AWS, Azure or Google Cloud Platform, Knowledge of CI/CD and deployment automation, Experience working with Git, Knowledge of AI/ML model monitoring in production 📃 Skills: Python, Docker, AWS, Azure, GCP, CICD, Git, MLOps, MachineLearning, Monitoring, Cloud 🏢 Description: O projekcie Poszukujemy MLOps / AI Engineera do realizacji innowacyjnych projektów dla sektora bankowego i finansowego. Osoba na tym stanowisku będzie odpowiedzialna za projektowanie, wdrażanie oraz utrzymanie rozwiązań opartych o sztuczną inteligencję, uczenie maszynowe oraz nowoczesne platformy danych. Będziesz współpracować z zespołami Data Science, Data Engineering i DevOps, wspierając cały cykl życia modeli AI – od budowy środowisk treningowych po wdrożenie modeli na środowiska produkcyjne. Twój zakres obowiązków Projektowanie i rozwój środowisk MLOps wspierających wdrażanie modeli AI/ML Automatyzacja procesów trenowania, testowania oraz wdrażania modeli Budowa i utrzymanie pipeline'ów ML oraz Data Pipelines Monitorowanie jakości, wydajności i stabilności modeli produkcyjnych Współpraca z Data Scientistami oraz zespołami developerskimi Implementacja rozwiązań opartych o Generative AI i Large Language Models (LLM) Zarządzanie infrastrukturą chmurową wspierającą rozwiązania AI Tworzenie dokumentacji technicznej oraz dobrych praktyk w zakresie AI Engineering Optymalizacja kosztów i wydajności środowisk AI/ML Nasze wymagania Minimum 3–4 lata doświadczenia na stanowisku MLOps Engineer, AI Engineer, Machine Learning Engineer lub pokrewnym Bardzo dobra znajomość Python Doświadczenie w budowie i utrzymaniu rozwiązań Machine Learning w środowiskach produkcyjnych Znajomość Docker oraz konteneryzacji aplikacji Doświadczenie z platformami chmurowymi AWS, Azure lub Google Cloud Platform Znajomość CI/CD oraz automatyzacji procesów wdrożeniowych Doświadczenie w pracy z Git Znajomość zagadnień związanych z monitoringiem modeli AI Umiejętność współpracy z zespołami Data Science i Engineering Znajomość języka angielskiego na poziomie B2–C1 Mile widziane Doświadczenie z MLflow Znajomość Apache Airflow Doświadczenie z Kubernetes Praktyczna znajomość PyTorch lub TensorFlow Doświadczenie z Large Language Models (LLM) Znajomość frameworków takich jak LangChain, LangGraph lub LlamaIndex Doświadczenie z bazami wektorowymi (Pinecone, Weaviate, ChromaDB, Qdrant) Znajomość rozwiązań RAG (Retrieval-Augmented Generation) Doświadczenie w projektach Generative AI Znajomość Apache Kafka Doświadczenie w sektorze bankowym lub finansowym Oferujemy Udział w nowoczesnych projektach związanych ze sztuczną inteligencją i uczeniem maszynowym Możliwość pracy zdalnej lub hybrydowej Elastyczne godziny pracy Stabilną współpracę przy długoterminowych projektach Możliwość rozwoju kompetencji w obszarze AI, MLOps i Generative AI Pracę z najnowszymi technologiami chmurowymi i rozwiązaniami AI Współpracę z ekspertami Data Science, AI oraz Cloud Engineering Realny wpływ na rozwój innowacyjnych produktów i usług Atrakcyjne wynagrodzenie adekwatne do doświadczenia i kompetencji Jeżeli chcesz rozwijać rozwiązania oparte na sztucznej inteligencji, wdrażać modele ML na skalę produkcyjną oraz uczestniczyć w projektach wykorzystujących Generative AI i LLM – zapraszamy do aplikowania.

🏢 Summary: DevOps Engineer role focused on designing and maintaining AI-driven CI/CD pipelines and deploying machine learning models across cloud and hybrid environments. The position involves integrating AI/ML tools into DevOps processes, optimizing infrastructure for AI workloads, and ensuring security and high availability. The engineer will work with modern cloud platforms and data technologies in international, agile projects. 🗂️ Requirements: Bachelor’s degree in Engineering, IT, Science or related field, Minimum 5 years of experience in DevOps or similar role, Hands-on experience with DevOps tools in AI/ML workflows, Experience with cloud platforms and AI/ML services, Experience deploying and scaling ML models in production, Proficiency in scripting or programming languages, Experience implementing automated testing for AI workflows, Knowledge of secure environments for AI-driven systems 📃 Skills: Jenkins, GitHubActions, Kubernetes, Docker, Terraform, AWS, Azure, GCP, MLflow, Kubeflow, Airflow, Python, Bash, YAML, TensorFlow, PyTorch, Scikit-learn, Grafana, AIOps 🏢 Description: About the role As a DevOps Engineer with AI integration skills, you will collaborate across multiple implementation streams and work closely with agile teams to achieve project and client goals. We are looking for passionate engineers ready to move our projects to the next level by leveraging modern technology stacks and AI-driven solutions. You will participate in international projects based on the latest data technologies and cloud platforms. Your key responsibilities Design and maintain CI/CD pipelines incorporating AI/ML tools and frameworks. Collaborate with AI teams to deploy and scale machine learning models in production environments. Integrate AI-based monitoring, alerting, and analytics tools to improve pipeline visibility and enable predictive analysis. Optimize infrastructure resource utilization for AI applications across cloud, on-premises, and hybrid environments. Ensure strong security practices within AI-driven pipeline ecosystems. Troubleshoot pipeline and infrastructure issues, especially those involving AI components, and ensure high availability. Monitor system performance and implement improvements using AI-enhanced tools. Skills and attributes for success Hands-on experience with DevOps tools such as Jenkins, GitHub Actions, Kubernetes, Docker, and Terraform. Strong understanding of cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services. Familiarity with AI workflow tools such as MLflow, Kubeflow, or Airflow. Proficiency in scripting and programming languages (Python, Bash, YAML, etc.). Ability to implement automated testing frameworks for validating AI models and workflows. Experience building secure environments for AI-driven systems. Experience integrating AI-powered monitoring tools (AIOps, Grafana with ML plugins, or custom AI diagnostics). Requirements Bachelor’s degree in Engineering, IT, Science, or a related technical field. At least 5 years of experience in a corporate IT environment in a similar role. Proven experience with DevOps tools and frameworks used in AI/ML workflows. Strong communication skills and ability to collaborate with global teams. Nice to have Certifications in DevOps or AI/ML (e.g., Kubernetes, AWS Machine Learning Specialty). Experience working with AIOps platforms. Knowledge of specialized data pipeline automation tools for machine learning. Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn in production environments.

🏢 Summary: Technical leadership role combining hands-on DevOps/SRE engineering with team management to build and operate large-scale GPU infrastructure for AI workloads. Focused on infrastructure automation, reliability, observability, and high-performance networking across complex production environments. Responsible for shaping IaC standards, CI/CD, and operational excellence for software-defined, GPU-based platforms. 🗂️ Requirements: 8+ years in DevOps, SRE, or Platform Engineering, 3+ years in technical leadership role, Experience with large-scale infrastructure automation, Proficiency in Infrastructure as Code tools, Experience with GitOps and CI/CD, Hands-on experience with Kubernetes, Experience with GPU technologies, Scripting or programming in Python, Go, or Bash, Experience with bare-metal provisioning, Knowledge of observability and monitoring tools, Understanding of distributed systems reliability, Experience with high-performance networking technologies, Ability to lead technical discussions and mentor engineers, English proficiency at communicative level 📃 Skills: Terraform, Ansible, Pulumi, Crossplane, GitOps, Kubernetes, NVIDIA, MIG, Python, Go, Bash, Prometheus, Grafana, Loki, OpenTelemetry, RDMA, InfiniBand, RoCE, CI/CD 🏢 Description: About the role We are looking for a Lead DevOps Engineer to provide technical leadership for DevOps and Site Reliability Engineering practices supporting large-scale GPU infrastructure used for AI training and inference workloads. This role combines hands-on engineering with team leadership. You will be responsible for shaping automation standards, improving platform reliability, and leading a team working on software-defined infrastructure, high-performance networking, observability, and operational excellence across complex production environments. Responsibilities Lead, mentor, and support a team of DevOps and SRE engineers working across the full lifecycle of GPU infrastructure platforms Design and implement Infrastructure as Code solutions for provisioning and managing bare-metal GPU servers, networking, storage, and cluster orchestration components Build and improve CI/CD pipelines for infrastructure, platform services, and internal tooling Develop and maintain monitoring, logging, alerting, and observability solutions for large-scale GPU environments Define and track SLIs/SLOs , improve incident response processes, and contribute to post-incident reviews and long-term reliability improvements Work closely with Infrastructure, Networking, Facilities, and AI/ML teams to ensure stable and scalable platform operations Automate operational processes such as cluster scaling, firmware and BIOS updates, hardware diagnostics, and capacity planning Support DevSecOps practices, including infrastructure hardening, vulnerability management, and compliance automation Identify operational inefficiencies and reduce repetitive manual work through automation Evaluate and introduce new tools and solutions related to GPU infrastructure, orchestration, and cloud-native operations Requirements 8+ years of experience in DevOps, SRE, Platform Engineering , or a similar area At least 3 years of experience in a technical lead, lead engineer, or team leadership role Strong practical experience with infrastructure automation in large-scale or complex production environments Very good knowledge of Terraform, Ansible, Pulumi, Crossplane , or similar Infrastructure as Code tools Experience with GitOps , configuration management, and CI/CD practices Hands-on experience with Kubernetes Experience working with GPU-related technologies such as NVIDIA GPU Operator, device plugins, MIG, or time-slicing Good scripting or programming skills in Python, Go, or Bash Experience with bare-metal provisioning, infrastructure automation, or data center environments Good knowledge of observability tools such as Prometheus, Grafana, Loki, and OpenTelemetry Good understanding of distributed systems reliability and production incident management Experience with high-performance networking technologies such as RDMA, InfiniBand, or RoCE will be a strong advantage Ability to lead technical discussions, support team development, and communicate effectively with both technical and business stakeholders English proficiency at least at a communicative level is required, as you will be working in an international team Nice to have Experience in AI infrastructure, HPC environments, hyperscale infrastructure, or data center operations Familiarity with orchestration and scheduling tools such as Slurm, Ray, Run:ai, KServe , or Kubernetes-based schedulers Experience integrating telemetry from power, cooling, or environmental systems Experience building internal platforms or self-service tools for engineering or research teams Understanding of security, compliance, and audit requirements in regulated or security-sensitive environments What we offer Benefits package Opportunity to shape the DevOps and SRE foundation for advanced GPU infrastructure supporting AI workloads Real impact on the scalability, reliability, and operational standards of next-generation compute environments Collaboration with experienced engineers across infrastructure, platform, and AI domains A dynamic environment with space for ownership, technical leadership, and professional growth

🏢 Summary: Long-term B2B opportunity for an AI DevOps Lead Engineer to design and manage cloud infrastructure on Azure and GCP, focusing on IaC, CI/CD, and Kubernetes clusters. The role centers on building secure, scalable environments, automating processes, and enhancing monitoring and security frameworks. Hybrid work model with strong emphasis on cloud-native and DevOps best practices. 🗂️ Requirements: 4+ years in DevOps, SRE, or Cloud Engineering, Strong knowledge of Linux/UNIX, Production experience with GCP and/or Azure, Experience managing GKE and/or AKS clusters, Proficiency in Terraform for Infrastructure as Code, Experience building CI/CD pipelines with Jenkins, Scripting skills in Python and/or Bash 📃 Skills: GCP, Azure, GKE, AKS, Terraform, Jenkins, Python, Bash, Linux, Kubernetes, CI/CD, IaC 🏢 Description: Introduction & Summary: We are seeking an accomplished AI DevOps Lead Engineer with a strong foundation in cloud infrastructure management and DevOps practices. The ideal candidate will have over 4 years of experience in DevOps, SRE, or Cloud Engineering roles, with a proven record of designing and implementing robust cloud solutions, particularly on GCP and Azure platforms. Strong expertise in Infrastructure as Code (IaC) and CI/CD pipeline management is imperative, along with scripting capabilities in Python and Bash. What we offer: Long Term B2B Contract Rate: 200 PLN/ H +VAT Hybrid Cracow ( 1-2 times per week) Main Responsibilities: Design, build, and manage core infrastructure on Azure using IaC principles. Administer and enhance GKE and AKS clusters, ensuring security, scalability, and resilience. Evolve Jenkins pipelines and developer tooling for improved automation and efficiency. Implement security controls and automate vulnerabilities remediation. Develop a robust monitoring and alerting framework for operational visibility. Implement security gateways for improved governance. Key Requirements: 4+ years of experience in a DevOps, SRE, or Cloud Engineering role. Deep knowledge of Linux/UNIX operating systems. Production experience with GCP and/or Azure, including management of clusters (GKE, AKS). Strong proficiency with Infrastructure as Code using Terraform. Proven experience with CI/CD pipeline development using Jenkins. Scripting and automation skills in Python and/or Bash. Nice to Have: Experience with monitoring tools like Prometheus, Grafana, and Loki. Familiarity with container management using Docker. Knowledge of additional cloud services and platforms. Other Details: This position offers the opportunity to work in a dynamic environment that fosters innovation and collaboration. Candidates can work remotely or on-site, depending on personal preferences; flexibility in schedule is provided to facilitate a productive work-life balance.

🏢 Summary: Remote AI Senior DevOps Engineer role focused on building and automating CI/CD and MLOps pipelines to enable seamless ML model deployment from training to production. The position bridges AI development and operations, emphasizing infrastructure as code, monitoring, DevSecOps, and scalable cloud environments. It involves close collaboration with AI teams to create a self-service model deployment platform. 🗂️ Requirements: 6–8 years experience in DevOps or SRE roles, Minimum 2 years experience in MLOps or AI/ML workloads, Expertise in Jenkins, GitHub Actions, or GitLab CI/CD, Hands-on experience with Azure DevOps, Hands-on experience with Terraform, Advanced knowledge of Docker and Kubernetes, Experience setting up Prometheus and Grafana dashboards, Experience with MySQL, PostgreSQL, or MongoDB, Familiarity with Ansible, Chef, or Puppet, Experience with SAST/DAST and vulnerability scanning in CI/CD, Experience with dataset and model versioning tools, Professional English C1 level 📃 Skills: Azure, Terraform, CloudFormation, Jenkins, GitHub, GitLab, Docker, Kubernetes, Prometheus, Grafana, MySQL, PostgreSQL, MongoDB, Ansible, Chef, Puppet, SAST, DAST, DVC, CI/CD, MLOps 🏢 Description: This is a remote position. Virtusa is seeking an AI Senior DevOps Engineer to bridge the gap between AI development and production-grade operations. You will be responsible for building the automated "highways" that allow ML models to flow from training to deployment seamlessly. This role requires a strong DevOps foundation combined with an understanding of the unique challenges of MLOps, such as GPU resource management, model versioning, and performance monitoring. Key Responsibilities: CI/CD & MLOps Pipelines: Build and maintain automated pipelines for ML models using Azure DevOps, GitHub Actions, or Jenkins. Workflow Automation: Automate model validation, packaging, and deployment workflows to ensure rapid iteration cycles. Infrastructure as Code (IaC): Use Terraform or CloudFormation to provision and manage cloud-native infrastructure, focusing on high-availability and scalability. Monitoring & Observability: Set up comprehensive monitoring for infrastructure (CPU/GPU/Memory) and model performance (latency and drift) using Prometheus and Grafana. DevSecOps Implementation: Integrate security into the heart of the pipeline, including secret management, IAM role configuration, and vulnerability scanning. Collaboration: Work closely with Data Scientists and AI Engineers to enable a self-service platform for model deployment. Requirements 6–8 years of experience in DevOps/SRE roles, with a minimum of 2 years focused on MLOps or supporting AI/ML workloads. Deep expertise in Jenkins, GitHub Actions, or GitLab CI/CD. Hands-on proficiency with Azure DevOps and Terraform (CloudFormation is a strong plus). Advanced knowledge of Docker and Kubernetes for managing distributed AI applications. Proven experience setting up Prometheus and Grafana dashboards for technical and model-specific metrics. Practical experience managing or connecting to MySQL, PostgreSQL, or MongoDB. Familiarity with Ansible, Chef, or Puppet for automated environment setup. Hands-on experience with SAST/DAST tools and automated vulnerability scanning within CI/CD pipelines. Experience with versioning tools for datasets and models (e.g., DVC or similar pipeline versioning logic). Professional English (C1) for seamless interaction with global delivery teams. Benefits Professional training programs Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row

🏢 Summary: The offer is for an AI DevOps Lead Engineer responsible for designing and managing cloud infrastructure on Azure and GCP with a strong focus on Infrastructure as Code and CI/CD automation. The role involves leading infrastructure initiatives, administering Kubernetes clusters, and implementing secure, scalable, and resilient cloud solutions. It is a long-term B2B contract with a hybrid work model in Cracow. 🗂️ Requirements: 4+ years experience in DevOps, SRE, or Cloud Engineering, Strong knowledge of Linux/UNIX systems, Production experience with GCP and/or Azure, Experience managing GKE and/or AKS clusters, Proficiency in Infrastructure as Code with Terraform, Experience building and maintaining CI/CD pipelines with Jenkins, Scripting skills in Python and/or Bash 📃 Skills: GCP, Azure, GKE, AKS, Terraform, Jenkins, Python, Bash, Linux, UNIX, CI/CD, IaC 🏢 Description: We are seeking an accomplished AI DevOps Lead Engineer with a strong foundation in cloud infrastructure management and DevOps practices. The ideal candidate will have over 4 years of experience in DevOps, SRE, or Cloud Engineering roles, with a proven record of designing and implementing robust cloud solutions, particularly on GCP and Azure platforms. Strong expertise in Infrastructure as Code (IaC) and CI/CD pipeline management is imperative, along with scripting capabilities in Python and Bash. What we offer: Long Term B2B Contract Rate: 200 PLN/ H +VAT Hybrid Cracow ( 1-2 times per week) Main Responsibilities: Design, build, and manage core infrastructure on Azure using IaC principles. Administer and enhance GKE and AKS clusters, ensuring security, scalability, and resilience. Evolve Jenkins pipelines and developer tooling for improved automation and efficiency. Implement security controls and automate vulnerabilities remediation. Develop a robust monitoring and alerting framework for operational visibility. Implement security gateways for improved governance. Key Requirements: 4+ years of experience in a DevOps, SRE, or Cloud Engineering role. Deep knowledge of Linux/UNIX operating systems. Production experience with GCP and/or Azure, including management of clusters (GKE, AKS). Strong proficiency with Infrastructure as Code using Terraform. Proven experience with CI/CD pipeline development using Jenkins. Scripting and automation skills in Python and/or Bash. Nice to Have: Experience with monitoring tools like Prometheus, Grafana, and Loki. Familiarity with container management using Docker. Knowledge of additional cloud services and platforms.

🏢 Summary: The offer is for a Senior DevOps Engineer responsible for designing, building, and operating secure, scalable cloud infrastructure for AI-driven automation platforms. The role focuses on Infrastructure as Code, CI/CD, monitoring, and automation in enterprise cloud environments, ensuring reliability, security, and compliance. It combines hands-on engineering with ownership of mission-critical services across their full lifecycle. 🗂️ Requirements: University degree in informatics or equivalent professional experience, Minimum 7 years of DevOps or infrastructure experience, Proven experience with Infrastructure as Code using Terraform, Experience with CI/CD tools such as Jenkins or GitHub Actions, Hands-on experience with AWS or Azure cloud services, Experience with DevOps workflows and automated incident response, Experience managing enterprise private cloud environments, Knowledge of secure service-to-service communication patterns, Knowledge of modern authentication protocols, Experience with monitoring, logging, and alerting systems, Experience with Python or another programming language, Understanding of AI technologies and AI process automation, Fluency in Polish and English (minimum B2) 📃 Skills: Terraform, Jenkins, GitHub, AWS, Azure, Python, CI/CD, DevOps, IaC, Monitoring, Logging, Alerting, Authentication, AI, Cloud 🏢 Description: As a Senior DevOps Engineer (AI & Automation Platform), you will be responsible for building and maintaining secure, scalable cloud infrastructures that power AI-driven automation. In this role, you will design and operate enterprise-ready solutions, implement Infrastructure as Code practices, and drive automation across systems and workflows. You will collaborate with internal teams and external vendors, ensuring performance, reliability, and compliance while mentoring colleagues and fostering an agile, innovation-oriented culture. This position is ideal for a hands-on engineer with strong analytical skills, a passion for automation, and the ability to take ownership of mission-critical services. Your Key Responsibilities Building and maintaining scalable and reliable cloud infrastructure for AI process automation platforms Ensuring operable and securing cloud-based solution architecture for custom-developed, open-source, and off-the-shelf applications Acting as technical consultant for internal colleagues and collect their feedback to ensure a successful user experience Establishing and maintaining logging, monitoring and alerting systems to proactively identify and resolve performance issues Taking on the technical responsibility of applications throughout the life cycle as part of a DevOps team Driving improvements of the automation level of our operations towards self-service Close collaboration with external software vendors for managing, developing, and maintaining IT systems Building and maintaining disaster recovery and business continuity plans for mission-critical applications and infrastructure Ensuring compliance with security policies and standards, working with security and compliance teams as necessary Your Qualifications University degree in (business) informatics or alternative training with relevant professional experience in this field At least 7 years of relevant professional experience in this field Strong automation and infrastructure as code mindset backed by proven experience in using Terraform and CI/CD technologies like Jenkins or GitHub Actions Experience with DevOps workflows for infrastructure management and automated incident response Proven experience in installing, configuring, maintaining and managing support operations with third party software in secured and enterprise ready private cloud environments Profound knowledge about common patterns for secure service-to-service connectivity and modern authentication protocols Familiarity with common monitoring, logging, and alerting solutions Hands-on experience working with managed cloud services (AWS or Azure preferred), including compute, storage, databases, and AI services Strong understanding of latest AI technology, like AI Agents, in combination with AI process automation Experience with an additional programming language such as Python Fluency in both Polish and English, with a minimum of B2 level proficiency Knowledge of German is a plus Ability and willingness to coach and to take responsibility for services Strong analytical skills with the ability to collect, organize, analyze and disseminate significant amounts of information with attention to detail and accuracy Eager to learn new technologies and skills (T-Shape philosophy) Proficiency in agile methodologies, with experience working effectively within agile teams and environments, fostering an agile mindset in daily work Willingness to travel up to 10%  of the time for work Our Offer Be a part of a global company & international team with a diverse variety of backgrounds, skills and views. As part of our IT team, you will actively shape the technology and solutions used by Schaeffler Grow with us! Get access to training platforms, internal & external trainings, supporting experts and the real-life challenges , where you will put all your skills in practice. We work in a hybrid working model (or a fully remote in a special cases) with flexible working hours . Our modern office is located in the center of Wroclaw . We offer attractive benefits package, such as medical and dental care , sports card, life insurance for you and your family. We are also providing access to our Mental Comfort Program. Our Cafeteria Platform allows you to choose from various benefit options with points monthly added to your account. Haven’t found what you are looking for? Our concierge will be happy to help! Join our CSR activities, such as tree planting, riverside cleanup, or participate in other charity events. Spend some time with your work colleagues during integrational events such as mountain trekking, city games and workshops. You can join also one of our many Passion Clubs like Foodies, Sports Team and Language Clubs as well!

🏢 Summary: The offer is for a Lead DevOps Engineer to design, implement, and maintain Azure-based DevOps solutions within an agile product team. The role focuses on infrastructure as code, CI/CD pipeline implementation, cloud resource optimization, monitoring, and ensuring security and reliability across Azure environments. It also includes technical leadership and process automation initiatives. 🗂️ Requirements: 5+ years of DevOps experience in agile environments, Expertise in Azure DevOps, Strong experience with Terraform or OpenTofu, Hands-on experience with Datadog, Experience managing Azure resources (Container Apps, App Configuration, Key Vault), Familiarity with Cosmos DB and Data Lake, Knowledge of at least one programming language (e.g., C#), Azure or DevOps certification, English proficiency B2 or higher 📃 Skills: Azure, AzureDevOps, Terraform, OpenTofu, Datadog, CI/CD, ContainerApps, CosmosDB, DataLake, AppConfiguration, KeyVault, C#, IaC 🏢 Description: We are seeking a skilled Lead DevOps Engineer to join our agile product development team and take charge of designing, implementing, and maintaining robust DevOps solutions. This role involves collaborating closely with product owners, front-end, back-end, and other DevOps professionals to ensure seamless integration and high-quality deliverables. Responsibilities Develop and manage infrastructure as code (IaC) using Terraform/Opentofu for Azure (azurerm/azapi) Design and implement Azure Pipelines in Azure DevOps for CI/CD processes Leverage Datadog to monitor and ensure the performance and reliability of applications Optimize and manage Azure resources such as Container Apps, Cosmos DB, Data Lake, App Configuration, and Key Vault Collaborate effectively with agile product teams to align DevOps strategies with business objectives Work cross-functionally to troubleshoot, resolve, and prevent operational issues Ensure a high standard of system security and compliance within Azure environments Provide mentorship and technical guidance to teammates regarding DevOps practices Proactively identify and implement opportunities for process improvements and automation Requirements 5+ years of experience working as a DevOps Engineer in agile environments Expertise in Azure DevOps, Terraform, and Datadog Competency in Azure resources, including Container Apps, App Configuration, and Key Vault Familiarity with additional Azure services like Cosmos DB and Data Lake Understanding of at least one programming language such as C# Capability to work effectively within cross-functional teams and adapt to changing workflows Strong problem-solving and communication skills Relevant certification in Azure or DevOps practices English proficiency at B2 level or higher We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: The role involves owning the full MLOps lifecycle for an AI-powered sports highlights platform, from model research and training to production deployment and scalable cloud infrastructure. You will build and maintain ML pipelines, automate workflows across Computer Vision and NLP, and ensure reliable CI/CD processes in a high-uptime environment. 🗂️ Requirements: 4+ years experience in MLOps, DevOps, ML Engineering or similar role, Experience in large-scale, high-uptime production cloud environments, Strong knowledge of Linux, Experience with Docker, Experience with Kubernetes, Experience building CI/CD pipelines for distributed systems, Proficiency in Python scripting, Experience with Terraform, Understanding of machine learning fundamentals and frameworks 📃 Skills: Python, Linux, Docker, Kubernetes, Terraform, CI/CD, ClearML, W&B, SageMaker, Azure, ComputerVision, NLP, MLOps 🏢 Description: We’re seeking a skilled and motivated MLOps Engineer to join a fast-moving team building an AI-powered platform for automatic sports highlights generation. In this role, you’ll take ownership of the full MLOps lifecycle—from research and model training to production deployment and scalable infrastructure. You’ll design and maintain robust ML pipelines, automate workflows across Computer Vision, NLP, and Data Science, and build reliable CI/CD processes that keep high-uptime systems running smoothly. Your work will help deliver cutting-edge AI experiences at cloud scale, powering innovation and performance across the entire platform. Responsibilities Own and manage every aspect in the MLOps life cycle for our AI-based automatic sports highlights generation platform Design, implement and maintain our whole ML infrastructure, from research to production and from model training to data engineering Automate and innovate workflows such as serving and training pipelines for multidisciplinary ML algorithms including Computer Vision, NLP and Data Science Build and maintain CI/CD pipelines, releases and Source Code workflows Requirements 4+ years of experience as an MLOps engineer, DevOps engineer, ML Engineer, or in a similar field Experience in a large, complex, large-scale, high-uptime production Cloud environment Core understanding of Linux OS, Docker components, and Kubernetes Experience with CI/CD pipelines for distributed production systems Experience with Python scripting Work experience with Terraform Working with MLOps platforms such as Experiment Tracking, Model Registry, feature Store - an advantage (e.g ClearML , W&B, Aws Sagemaker) Highly motivated, goal-driven, innovative, curious, and open-minded Will be a plus Working with Azure Cloud in a high-scale production environment Understanding of AI and machine learning fundamentals, concepts and frameworks What we offer Competitive salary range Medical insurance Paid vacation and sick leaves MultiSport card Top equipment kit, co-workings Hybrid set of works (Office location: Warsaw) Collaborative and innovative work environment Career growth and development opportunities A chance to work with giants of the sports industry About the project Our partner leads the industry in generating dynamic sports videos for every digital destination. Their cutting-edge AI and Machine Learning technologies analyse live sports broadcasts from over 250 leagues and broadcast partners, including iconic names like the NBA, NHL, ESPN, FIBA and Bundesliga, to create personalized, short-form videos in real-time. The solution empowers media rights owners to unlock new revenue streams and deliver a tailored fan experience across every digital platform. Join the high-profile Engineering team and discover the forefront of sports content innovation.