Job
Description
What You'll Do:At Meltwater, our DevOps Engineers play a vital role in building and maintaining robust, scalable, and highly available infrastructures that support our global client baseIn this role, you will design, test, maintain, and operate cutting-edge DevOps architectures that process billions of documents per day through advanced Machine Learning workflowsall while ensuring a 99.999% uptime.As a key member of our engineering team, you will:Develop, test and maintain highly scalable, fault-tolerant DevOps architectures tailored for large-scale data processing and machine learning applications.closely with cross-functional development teams, taking full ownership of your subsystems and infrastructure.Participate in on-call rotations, being ready to troubleshoot and resolve real-time issues efficiently.Explore opportunities to enhance our technology stack by modifying open-source libraries and integrating innovative solutions.Continuously optimize quality, performance, reliability, and security across our systems.Champion a strong DevOps culture by implementing best practices in continuous integration (CI), continuous deployment (CD), infrastructure as code (IaC), and automated testing.We are looking for a proactive, fast-learning engineer who thrives in a collaborative, innovative environmentIf you have a passion for distributed AI systems and a drive to push the boundaries of technology, this is the perfect opportunity for you!What You'll Bring:E/BSolid theoretical knowledge of fundamental programming principles.2-4 years of hands-on experience in software engineering, DevOps, or cloud infrastructure.Hands-on experience with Python (1+ years) for scripting and automation.Experience with core Java (2+ years) for backend development (JUnit, Maven, Spring Boot, REST APIs),Strong understanding of DevOps principles (2+ years) and a commitment to continuous learning and improvement.Proven expertise with Terraform (2+ years) for infrastructure as code.Experience (2+ years) with cloud platformspreferably Azure, but AWS is also valued.Proficiency in Docker containerization (2+ years) for building scalable, portable applications.Knowledge of Kubernetes (K8s) development (1+ years) for container orchestration.Familiarity with bash/shell scripting for automation.Practical experience in:CI/CD pipelines (GitHub Actions is a plus).Observability (logging, monitoring, and alerting).VPC, EC2, and cloud networking (routing, load balancing, security).Nice to Have:Experience with messaging systems (Kafka, RabbitMQ, ActiveMQ, or Kinesis) for real-time data processing.Familiarity with serverless computing technologies (AWS Lambda, Azure Functions).Experience with NLP/ML/LLMs pipelines, particularly in AI-driven applicationsInterest or experience in Machine Learning Operations (MLOps) to streamline AI/ML workflows.
