At Meltwater, our DevOps Engineers play a vital role in building and maintaining robust, scalable, and highly available infrastructures that support our global client base
In 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 environment
If 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/B
Solid 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 applications
Interest or experience in Machine Learning Operations (MLOps) to streamline AI/ML workflows.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: DevOpsRole: DevOps EngineerEmployement Type: Full time
We believe that business strategy will be increasingly shaped by insights from the growing world of online data that lies outside of internal reporting systems.