Distributed Systems Engineer III at Mozn

Worldwide

<p>About Mozn</p><p>MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.<br /><br />We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.<br /><br />If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.</p><p></p><p>About the role</p><p>We are looking for a highly motivated Distributed Systems Engineer III to join our Cloud Platform Engineering team. </p><p>This role focuses on building and operating reliable, scalable, and resilient cloud platforms for distributed and data-intensive workloads. You will work across Kubernetes, cloud infrastructure, messaging systems, databases, automation, and platform reliability. </p><p>The role requires strong hands-on experience with Kafka, Kubernetes, and at least one relational database such as MySQL or PostgreSQL, along with a solid understanding of distributed-systems fundamentals. </p><p>As our platform evolves, you will also contribute to AI and data infrastructure, helping build the underlying platform capabilities required to run data-intensive and AI</p><p></p><p>What you'll do</p><p>Cloud Platform &amp; Distributed Systems </p><ul><li>Build, operate, and continuously improve production cloud-native platforms running distributed workloads. </li></ul><ul><li>Work hands-on with Kubernetes, including upgrades, node pools, workload lifecycle, troubleshooting, and platform operations. </li></ul><ul><li>Deploy and manage workloads using ArgoCD, Helm, GitOps, Terraform, and automation. </li></ul><ul><li>Design and operate systems with a focus on scalability, availability, resilience, performance, and operational simplicity. </li></ul><ul><li>Troubleshoot complex issues across Kubernetes, cloud infrastructure, networking, storage, applications, and distributed services. </li></ul><p>Kafka &amp; Data Infrastructure </p><ul><li>Operate and troubleshoot Apache Kafka in production across high-throughput and distributed workloads. </li></ul><ul><li>Work with topics, partitions, replication, consumer groups, retention, throughput, latency, and failure recovery. </li></ul><ul><li>Integrate Kafka with databases and applications using technologies such as Kafka Connect, Debezium, or similar CDC/event-streaming platforms. </li></ul><ul><li>Operate and troubleshoot MySQL and/or PostgreSQL, including replication, high availability, backup, recovery, performance, and migrations. </li></ul><ul><li>Support data-intensive workloads and analytical platforms such as StarRocks, ClickHouse, Apache Doris, or similar technologies. </li></ul><p>Reliability, DR &amp; Multi-Tenant Platforms </p><ul><li>Design and operate platforms that remain resilient across node, service, zone, and infrastructure failures. </li></ul><ul><li>Implement and validate backup, recovery, disaster recovery, failover, and business-continuity capabilities. </li></ul><ul><li>Understand the fundamentals of multi-zone, multi-region, and active-active architectures and apply them where appropriate. </li></ul><ul><li>Build platforms that support multiple tenants and workloads, with appropriate isolation, scalability, resource management, and reliability. </li></ul><ul><li>Participate in DR exercises, failure simulations, migrations, and other resilience initiatives. </li></ul><ul><li>Understand distributed-system trade-offs involving replication, consistency, availability, partitioning, fault tolerance, latency, and throughput. </li></ul><p>Automation, Observability &amp; Operations </p><ul><li>Automate infrastructure and platform lifecycle operations using Terraform, Python, Bash, Go, or similar technologies. </li></ul><ul><li>Build reliable deployment and GitOps workflows and reduce manual operational effort. </li></ul><ul><li>Implement effective monitoring, logging, alerting, and observability for distributed workloads. </li></ul><ul><li>Participate in production incident response, root-cause analysis, and long-term reliability improvements. </li></ul><p>AI &amp; Emerging Platform Infrastructure </p><ul><li>Contribute to the infrastructure needed to support AI, machine-learning, and data-intensive workloads. </li></ul><ul><li>Help evolve cloud and Kubernetes platforms to support AI workloads, data pipelines, model-serving infrastructure, and associated platform services. </li></ul><ul><li>Understand the infrastructure requirements around compute, GPUs, networking, storage, data movement, observability, and workload isolation for AI platforms. </li></ul><ul><li>Work with engineering teams to build reusable platform capabilities that enable AI and data workloads to run reliably at scale. </li></ul><ul><li>Stay current with emerging infrastructure patterns across AI platforms, distributed data systems, and cloud-native technologies. </li></ul><p></p><p>Requirements</p><ul><li>4–7 years of experience in Platform Engineering, Infrastructure Engineering, Distributed Systems, SRE, Backend Engineering, Data Infrastructure, or a related field. </li></ul><ul><li>Strong production experience with Apache Kafka — mandatory. </li></ul><ul><li>Hands-on production experience with Kubernetes — mandatory. </li></ul><ul><li>Strong experience with at least one of MySQL or PostgreSQL — mandatory. </li></ul><ul><li>Solid understanding of distributed-systems fundamentals including replication, partitioning, consistency, availability, fault tolerance, scalability, and failure recovery. </li></ul><ul><li>Experience with ArgoCD/GitOps and infrastructure-as-code such as Terraform. </li></ul><ul><li>Experience operating workloads on a public cloud such as GCP, OCI, AWS, or Azure. </li></ul><ul><li>Strong production troubleshooting and incident-resolution skills. </li></ul><ul><li>Experience with automation or scripting using Python, Bash, Go, Java, or similar languages. </li></ul><ul><li>Understanding of high-availability, disaster-recovery, and multi-tenant architecture fundamentals. </li></ul><ul><li>Experience with observability and operational tooling such as Prometheus, Grafana, OpenSearch/ELK, LGTM, or equivalent. </li></ul><ul><li>Strong understanding of infrastructure and networking fundamentals in cloud-native environments. </li></ul><p></p><p>Good to Have </p><ul><li>Experience with Kafka Connect, Debezium, Kafka Streams, or CDC platforms. </li></ul><ul><li>Experience with distributed analytical databases such as StarRocks, ClickHouse, Apache Doris, or similar. </li></ul><ul><li>Experience with Flink, Spark, or other distributed data-processing systems. </li></ul><ul><li>Experience executing large-scale data, database, application, or infrastructure migrations. </li></ul><ul><li>Experience with active-active, multi-zone, or multi-region systems. </li></ul><ul><li>Experience operating stateful workloads on Kubernetes. </li></ul><ul><li>Experience supporting AI/ML infrastructure or GPU-based workloads. </li><li>Experience with cloud networking, service mesh, ingress, load balancing, or storage platforms. </li><li>Contributions to Kubernetes, Kafka, distributed-systems, or other open-source infrastructure projects. </li></ul><p></p><p>Benefits</p><ul><li>You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.</li></ul><ul><li>You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.</li></ul><ul><li>The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best</li></ul><ul><li>You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.</li></ul><ul><li>We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.</li></ul>