DevOps Engineer with AI Integration Skills

🏢 Summary: Remote AI Lead DevOps Engineer role responsible for defining and executing the MLOps and CI/CD strategy for enterprise AI platforms. The position focuses on architecting secure, compliant, and fully automated ML lifecycle governance, ensuring auditability, reproducibility, and large-scale reliability. The role combines technical leadership with hands-on design of cloud-native, DevSecOps-driven AI infrastructure. 🗂️ Requirements: 8–10 years DevOps or Cloud Engineering experience, Minimum 3 years in technical leadership or architect role, Strong knowledge of end-to-end ML lifecycle, Expertise in CI/CD pipeline design and implementation, Advanced Infrastructure as Code experience, Experience with SAST and DAST implementation, Strong IAM and access control management in cloud, Ability to design observability frameworks for ML systems, Experience with configuration management in multi-cloud environments, Knowledge of database scaling and security, Experience implementing model governance and auditability practices 📃 Skills: MLOps, CI/CD, DevSecOps, Azure, AzureDevOps, GitHubActions, Jenkins, Terraform, CloudFormation, SAST, DAST, IAM, Ansible, Puppet, MySQL, PostgreSQL, MongoDB, Observability, Git 🏢 Description: This is a remote position. We are looking for an AI Lead DevOps Engineer to spearhead the MLOps strategy for our high-impact AI accounts. With 8–10 years of experience, you will provide the technical leadership necessary to design robust, compliant, and highly automated AI platforms. You aren't just managing pipelines; you are architect the entire lifecycle governance—ensuring reproducibility, audibility, and security at an enterprise scale. Key Responsibilities: Strategic Leadership: Provide technical direction for the DevOps squad, defining the CI/CD and MLOps roadmap for the account. Model Governance & Evaluation: Implement automated model evaluation pipelines to track accuracy, precision, and recall metrics in production. Enterprise Security: Lead the DevSecOps strategy, ensuring all AI deployments comply with enterprise security standards and global data regulations. Platform Enablement: Architect self-service platforms that allow ML engineers to deploy models with minimal friction while maintaining strict governance guardrails. Auditability & Reproducibility: Ensure that every ML experiment is fully auditable through sophisticated pipeline and dataset versioning strategies. Mentorship: Mentor senior and junior engineers, driving best practices in automation, IaC, and cloud-native architecture. Requirements 8–10 years of experience in DevOps/Cloud Engineering, with at least 3 years in a technical leadership or architect-level role. Deep understanding of the end-to-end ML lifecycle (training, validation, deployment, and retraining loops). Mastery across Azure DevOps, GitHub Actions, and Jenkins. Expert-level Terraform or CloudFormation skills, including modular architecture and cross-account cloud deployments. Significant experience implementing SAST/DAST tools and managing complex IAM/Access Control frameworks in a cloud environment. Ability to design custom observability frameworks that track model drift, pipeline failures, and infrastructure ROI. Advanced knowledge of configuration management tools like Ansible or Puppet for complex multi-cloud environments. Solid understanding of database scaling and security for MySQL, PostgreSQL, and MongoDB. Understanding of how DevOps practices support responsible AI (e.g., bias tracking and audit logs). Exceptional ability to collaborate with Architects and Data Scientists to translate high-level AI needs into operational reality. Native or C1-level English, with the ability to present technical strategies to senior 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: Junior DevOps Engineer role focused on supporting and automating cloud infrastructure for AI training and inference workloads. The position involves working with CI/CD pipelines, containerization, Infrastructure as Code, and monitoring systems in a hands-on learning environment. It offers growth in DevOps, platform engineering, and cloud operations. 🗂️ Requirements: 0–2 years in DevOps, IT operations, infrastructure, or system administration, Knowledge of Linux and terminal usage, Knowledge of Python for automation and scripting, Ability to write automation scripts, Practical knowledge of AWS and basic cloud services, Understanding of cloud infrastructure concepts, Knowledge of Docker and containerization, Basic understanding of CI/CD concepts, Ability to use Git, Basic understanding of networking, security, logging, and monitoring, Interest in Infrastructure as Code tools (Terraform or Ansible), Basic understanding of Kubernetes, Communicative English 📃 Skills: Linux, Python, AWS, Docker, CI/CD, Git, Terraform, Ansible, Kubernetes, Bash, Prometheus, Grafana, Loki, OpenTelemetry, GitHub, GitLab, Jenkins 🏢 Description: About the role We are looking for a Junior DevOps Engineer to support the development, automation, and maintenance of infrastructure used for AI training and inference workloads. In this role, you will work with experienced engineers on cloud and infrastructure automation, CI/CD pipelines, application environments, monitoring, and operational support. This is a hands-on position for someone who wants to grow in DevOps, platform engineering, cloud infrastructure, and modern operations. Responsibilities Support the maintenance and development of cloud and infrastructure environments Help prepare, maintain, and troubleshoot application environments Automate repetitive tasks using Python, Bash, and scripts Support the creation and maintenance of CI/CD pipelines Assist with Infrastructure as Code solutions for servers, networking, storage, and cluster components Monitor systems, analyze logs, and help troubleshoot technical issues Work with development, infrastructure, networking, and AI/ML teams on application deployment and platform operations Support the stability, security, and reliability of infrastructure Help identify manual processes that can be automated Document technical solutions, runbooks, and operational processes Requirements 0–2 years of experience in DevOps, IT operations, infrastructure, system administration, or a similar area Good knowledge of Linux and working in the terminal Good knowledge of Python for automation, scripts, and simple internal tools Ability to write clear scripts automating repetitive tasks Practical knowledge of AWS and basic cloud services Understanding of cloud environments and basic cloud infrastructure concepts Good knowledge of Docker and application containerization Basic understanding of CI/CD concepts Ability to work with Git Basic understanding of networking, security, logs, and monitoring Interest in Infrastructure as Code tools such as Terraform or Ansible Basic understanding of Kubernetes or willingness to learn Strong problem-solving attitude and eagerness to learn Ability to communicate clearly and work in a technical team Communicative English, as you will work in an international environment Nice to have First experience with Kubernetes, Terraform, Ansible, or GitOps Familiarity with monitoring tools such as Prometheus, Grafana, Loki, or OpenTelemetry Basic understanding of DevSecOps practices and vulnerability management Familiarity with AI infrastructure, GPU environments, HPC, or data center operations Experience with GitHub Actions, GitLab CI, Jenkins, or similar tools Interest in platform engineering, SRE, or large-scale infrastructure What we offer Benefits package Opportunity to learn from experienced infrastructure, platform, cloud, and AI engineers Work on modern infrastructure supporting AI workloads Space for professional growth in DevOps and platform engineering Remote or hybrid work from Poland

🏢 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 Cloud Developer responsible for building and deploying scalable, cloud-native backend applications with integrated AI components. The role focuses on Python and Django development, workflow orchestration, containerization, and cloud infrastructure. It involves developing REST APIs, automating workflows, and maintaining secure, high-performance cloud environments. 🗂️ Requirements: Strong Python programming, Hands-on Django experience, Experience with Django Rest Framework, Practical experience with Apache Airflow, Hands-on Docker experience, Experience with Kubernetes, Proficiency with Git, Solid Linux knowledge, Experience with cloud platforms (AWS, Azure, GCP, or private cloud) 📃 Skills: Python, Django, DRF, Airflow, Docker, Kubernetes, Git, Linux, AWS, Azure, GCP, REST 🏢 Description: Position Overview We are looking for a skilled AI Cloud Developer to join our team and support the design, development, and deployment of intelligent cloud-based applications. The ideal candidate has strong backend development skills in Python and Django , hands-on experience with modern cloud-native technologies, and an interest in integrating AI solutions into production systems. This role focuses on building scalable, secure, and automated solutions that combine backend engineering, workflow orchestration, containerization, and cloud infrastructure. Roles and Responsibilities Design, develop, and maintain backend applications using Python and Django . Build and optimize RESTful APIs using Django Rest Framework (DRF) . Integrate AI/ML components and services into cloud-based applications. Develop and manage workflow automation solutions using Apache Airflow . Deploy and maintain containerized applications using Docker and Kubernetes . Support cloud-native application architecture and scalability. Improve CI/CD and deployment processes. Monitor, troubleshoot, and optimize application performance in cloud environments. Collaborate with DevOps, infrastructure, and data teams. Create and maintain technical documentation. Required Skills and Experience Strong programming skills in Python . Hands-on experience with Django . Experience with Django Rest Framework (DRF) . Practical experience with Apache Airflow . Hands-on experience with Docker . Experience working with Kubernetes . Proficiency with Git version control. Solid understanding of Linux systems . Knowledge of cloud environments (AWS, Azure, GCP, or private cloud). Strong analytical and problem-solving skills. Ability to work independently and in a technical team. Nice to Have Experience with AI/ML integration in production systems . Familiarity with MLOps practices . Experience with Infrastructure-as-Code tools (e.g., Terraform, Ansible). Knowledge of CI/CD pipelines. Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK). Understanding of scalable cloud-native architecture patterns.

🏢 Summary: The role involves designing, implementing, and maintaining scalable cloud infrastructure and CI/CD pipelines, with a strong focus on Google Cloud Platform and Azure. The DevOps Engineer will automate deployments, manage infrastructure as code, and ensure reliability, security, and performance of cloud environments. The position requires close collaboration with development teams to improve deployment processes and platform stability. 🗂️ Requirements: Proven experience as DevOps Engineer or similar cloud role, Expert-level experience with Google Cloud Platform, Hands-on experience with Microsoft Azure, Experience with CI/CD tools (Azure DevOps, GitHub, GitHub Actions), Experience with Infrastructure as Code using Terraform, Scripting and automation skills using Python, Knowledge of cloud architecture and deployment best practices, Strong troubleshooting skills, English proficiency 📃 Skills: GCP, Azure, Terraform, Python, AzureDevOps, GitHub, GitHubActions, CI/CD, IaC 🏢 Description: About the Role We are looking for a skilled DevOps Engineer to join our technology team and help design, implement, and maintain scalable cloud infrastructure and modern CI/CD pipelines. In this role, you will work closely with development and platform teams to automate processes, improve deployment efficiency, and ensure the reliability and security of cloud-based systems. The ideal candidate has strong experience with cloud platforms, infrastructure as code, and modern DevOps practices, with particular expertise in Google Cloud Platform and CI/CD tooling. Key Responsibilities Design, implement, and maintain CI/CD pipelines using Azure DevOps , GitHub , and GitHub Actions . Build and manage scalable cloud infrastructure on Google Cloud Platform and Microsoft Azure . Develop and maintain infrastructure using Infrastructure as Code practices with Terraform . Automate operational and deployment processes using Python . Monitor and optimize cloud environments for performance, reliability, and cost efficiency. Collaborate with development teams to improve application deployment processes and platform reliability. Implement best practices in security, access control, and cloud governance. Troubleshoot infrastructure and deployment issues across environments. Required Skills & Experience Proven experience as a DevOps Engineer or in a similar cloud/infrastructure role. Strong hands-on experience with Google Cloud Platform at a principal or expert level . Solid experience with Microsoft Azure . Hands-on experience with CI/CD tools such as Azure DevOps , GitHub , and GitHub Actions . Strong knowledge of Infrastructure as Code tools, particularly Terraform . Good scripting and automation skills using Python . Experience with cloud architecture, automation, and deployment best practices. Strong troubleshooting and problem-solving skills. Ability to work collaboratively in cross-functional teams. Good communication skills and proficiency in English.

🏢 Summary: Hands-on DevOps Engineer role focused on building and operating automation, deployment, and reliability standards for large-scale GPU infrastructure supporting AI training and inference. The position involves Infrastructure as Code, CI/CD, observability, security, and low-level automation across bare-metal servers, networking, storage, and Kubernetes-based platforms. The role emphasizes reliability, scalability, and automation in complex, high-performance environments. 🗂️ Requirements: 4–7 years in DevOps, SRE, or Platform Engineering, Experience with infrastructure automation in production environments, Hands-on experience with Terraform or Ansible, Experience building and maintaining CI/CD pipelines, Knowledge of GitOps practices, Understanding of infrastructure security and vulnerability management, Experience with security tools (e.g., Snyk, CrowdStrike), Practical experience with Kubernetes, Experience with GPU technologies (e.g., NVIDIA GPU Operator, MIG), Scripting or programming skills in Python, Go, or Bash, Experience with bare-metal provisioning or low-level infrastructure automation, Knowledge of observability tools (Prometheus, Grafana, Loki, OpenTelemetry) 📃 Skills: Terraform, Ansible, Kubernetes, Python, Go, Bash, Prometheus, Grafana, Loki, OpenTelemetry, Snyk, CrowdStrike, NVIDIA, MIG, CI/CD, GitOps 🏢 Description: About the role We are looking for a DevOps Engineer to help build and operate automation, deployment, and reliability standards for large-scale GPU infrastructure used for AI training and inference workloads. In this role, you will work on software-defined infrastructure supporting GPU clusters, high-performance networking, storage platforms, and internal AI services. This is a hands-on position for someone who is comfortable working close to infrastructure, improving operational processes, and building reliable automation in a complex technical environment. Responsibilities Design, implement, and maintain 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 Support reliability initiatives by defining and tracking SLIs/SLOs , automating incident response, and contributing to post-incident analysis Automate operational tasks such as cluster scaling, firmware and BIOS updates, hardware validation, diagnostics, and capacity planning Work closely with Infrastructure, Networking, Facilities, and AI/ML teams to ensure stable and scalable platform operations Support DevSecOps practices, including infrastructure hardening, vulnerability management, and compliance automation Identify repetitive manual work and replace it with efficient automation Evaluate new tools and solutions related to GPU infrastructure, orchestration, and cloud-native operations Requirements 4–7 years of experience in DevOps, SRE, Platform Engineering , or a similar role Strong practical experience with infrastructure automation in complex production environments Good hands-on knowledge of Terraform, Ansible , or similar Infrastructure as Code tools Experience building and maintaining CI/CD pipelines and working with GitOps practices Good understanding of infrastructure security, vulnerability management, and security best practices Experience with security tools such as Snyk, CrowdStrike , or similar solutions Practical 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, low-level infrastructure automation, or data center operations Good knowledge of observability tools such as Prometheus, Grafana, Loki, and OpenTelemetry Ability to work independently, prioritize tasks, and communicate effectively with technical teams 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 teams Understanding of compliance and audit requirements in security-sensitive environments What we offer Benefits package Opportunity to work on advanced infrastructure supporting large-scale AI workloads Real impact on the reliability and scalability of next-generation compute environments Collaboration with experienced engineers across infrastructure, platform, and AI domains A fast-moving environment with space for ownership, technical input, and professional growth

🏢 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: DevOps Engineer role focused on supporting and scaling modern data platforms by combining DevOps practices with data engineering expertise. The position involves building and maintaining CI/CD pipelines, managing cloud-based data infrastructure, and ensuring reliable, automated data workflows. You will collaborate with data teams to optimize performance, scalability, and security of data solutions. 🗂️ Requirements: 4–5 years experience in DevOps or similar role, Hands-on experience with Databricks, Strong experience with AWS, Experience building and maintaining CI/CD pipelines with Jenkins, Background in data engineering or data platforms, Basic to intermediate Python knowledge, Understanding of ETL/ELT processes, Knowledge of distributed data systems 📃 Skills: Jenkins, Databricks, AWS, Python, CICD, ETL, ELT, DevOps, DataEngineering, Cloud, DistributedSystems 🏢 Description: About the Role We are looking for a DevOps Engineer with a strong data background to support and scale modern data platforms. In this role, you will work at the intersection of DevOps and Data Engineering , ensuring reliable, automated, and efficient data pipelines and environments. You will be responsible for maintaining and improving CI/CD processes, supporting cloud-based data platforms, and collaborating with data engineers and analytics teams to enable smooth data operations. Key Responsibilities Design, implement, and maintain CI/CD pipelines using Jenkins . Manage and optimize data platforms based on Databricks . Build and maintain cloud infrastructure on Amazon Web Services . Support deployment, monitoring, and troubleshooting of data pipelines and workflows. Collaborate closely with data engineers to improve reliability and performance of data solutions. Automate infrastructure and operational processes. Ensure best practices in security, scalability, and performance across the platform. Required Skills & Experience 4–5 years of experience in a DevOps Engineer or similar role. Hands-on experience with Databricks . Strong experience with Amazon Web Services . Experience building and maintaining CI/CD pipelines using Jenkins . Background in data engineering or experience working with data platforms. Basic to intermediate knowledge of Python . Understanding of data pipelines, ETL/ELT processes, and distributed data systems. Strong problem-solving skills and ability to troubleshoot complex issues. Good communication skills and ability to work in cross-functional teams.

🏢 Summary: Senior AWS DevOps Engineer role focused on designing, automating, and maintaining scalable cloud infrastructure and CI/CD pipelines for distributed applications. The position involves managing Kubernetes environments, implementing Infrastructure as Code, and improving reliability, security, and observability across AWS platforms. You will collaborate with engineering teams to enhance deployment processes and ensure high availability of production systems. 🗂️ Requirements: 5+ years DevOps or Cloud Engineering experience, Strong hands-on experience with AWS services, Experience with Kubernetes and containerized environments, Strong experience with Terraform and Infrastructure as Code, Experience building and maintaining CI/CD pipelines, Strong Linux administration skills, Scripting skills in Bash or Python, Experience with monitoring and logging tools, Knowledge of networking, security, and IAM, Experience with Git-based workflows 📃 Skills: AWS, Kubernetes, EKS, Docker, Terraform, CloudFormation, CICD, Linux, Bash, Python, CloudWatch, Prometheus, Grafana, ELK, Datadog, Git, IAM, Jenkins, GitHub, GitLab, AzureDevOps, Helm, ArgoCD, Serverless, Networking, Security 🏢 Description: About the Role We are looking for a Senior AWS DevOps Engineer to join a fast-paced international engineering team. The ideal candidate will be responsible for designing, implementing, automating, and maintaining cloud infrastructure and CI/CD ecosystems for highly scalable distributed applications. You will work closely with development, security, and infrastructure teams to improve deployment processes, system reliability, scalability, and operational efficiency across cloud environments. Key Responsibilities Design, build, and maintain scalable AWS cloud infrastructure Implement and optimize CI/CD pipelines for automated deployments Manage Kubernetes clusters and containerized workloads Develop Infrastructure as Code (IaC) solutions using Terraform or CloudFormation Improve system observability, monitoring, logging, and alerting Automate operational and deployment processes Ensure high availability, performance, and security of production systems Collaborate with development teams to support cloud-native application delivery Participate in troubleshooting, incident response, and root cause analysis Support platform reliability, scalability, and disaster recovery initiatives Required Skills & Experience 5+ years of experience in DevOps / Cloud Engineering roles Strong hands-on experience with AWS services Experience with Kubernetes (EKS preferred) and Docker Strong experience with Terraform and Infrastructure as Code Experience building and maintaining CI/CD pipelines Strong Linux administration and scripting skills (Bash/Python) Experience with monitoring and logging tools such as CloudWatch, Prometheus, Grafana, ELK, Datadog, etc. Experience with Git-based workflows and automation tools Good understanding of networking, security, IAM, and cloud best practices Experience working in Agile/Scrum environments Strong troubleshooting and communication skills Nice to Have AWS Certifications Experience with GitHub Actions, GitLab CI, Jenkins, or Azure DevOps Experience with serverless architectures Exposure to multi-cloud environments (AWS/Azure) Knowledge of security and compliance frameworks Experience with Helm, ArgoCD, or service mesh technologies

🏢 Summary: The offer is for a Data Engineer/DevOps professional to build and maintain scalable data platforms and cloud infrastructure, automate data workflows using CI/CD and Infrastructure as Code, and optimize data pipelines for high availability and security. The role focuses on managing data processing environments and supporting model deployment in collaboration with data teams. 🗂️ Requirements: Proficiency in Linux/Unix administration, Strong Shell scripting skills, Advanced knowledge of Python, Advanced knowledge of SQL, 3–5 years experience in Data Engineering or DevOps, Degree in Computer Science, Data Engineering, or related field 📃 Skills: Linux, Unix, Shell, Python, SQL, Azure, Spark, Databricks, Docker, Kubernetes, Terraform, Ansible, Hadoop, Kafka, CICD 🏢 Description: Key Responsibilities Infrastructure Management: Build and maintain scalable data platforms and cloud-based infrastructure. Automation: Implement CI/CD pipelines for data workflows and automate manual processes using Infrastructure as Code (IaC). Pipeline Optimization: Monitor, troubleshoot, and optimize data processing jobs to ensure high availability. Security & Compliance: Ensure data integrity and security across all environments. Collaboration: Work closely with Data Scientists and Engineers to streamline the deployment of data models. Requirements Systems & Scripting: Strong proficiency in Linux/Unix administration and Shell scripting. Programming: Advanced knowledge of Python and SQL . Mindset: Exceptional analytical and problem-solving skills. Education: Degree in Computer Science, Data Engineering, or a related technical field. Experience: 3–5 years of proven experience in Data Engineering or a DevOps-related role. Nice-to-have Cloud & Big Data: Hands-on experience with Azure , Apache Spark , and Databricks . DevOps Tools: Proficiency with Docker , Kubernetes , CI/CD tools, and IaC (e.g., Terraform, Ansible). Data Ecosystems: Familiarity with Big Data technologies such as Hadoop or Kafka .