[Hiring] Distributed Systems Engineer III @Mozn

Role Description

We are looking for a highly motivated Distributed Systems Engineer III to join our Cloud Platform Engineering team. 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.

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.

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.

What you'll do

• Cloud Platform & Distributed Systems
  • Build, operate, and continuously improve production cloud-native platforms running distributed workloads.
  • Work hands-on with Kubernetes, including upgrades, node pools, workload lifecycle, troubleshooting, and platform operations.
  • Deploy and manage workloads using ArgoCD, Helm, GitOps, Terraform, and automation.
  • Design and operate systems with a focus on scalability, availability, resilience, performance, and operational simplicity.
  • Troubleshoot complex issues across Kubernetes, cloud infrastructure, networking, storage, applications, and distributed services.
• Kafka & Data Infrastructure
  • Operate and troubleshoot Apache Kafka in production across high-throughput and distributed workloads.
  • Work with topics, partitions, replication, consumer groups, retention, throughput, latency, and failure recovery.
  • Integrate Kafka with databases and applications using technologies such as Kafka Connect, Debezium, or similar CDC/event-streaming platforms.
  • Operate and troubleshoot MySQL and/or PostgreSQL, including replication, high availability, backup, recovery, performance, and migrations.
  • Support data-intensive workloads and analytical platforms such as StarRocks, ClickHouse, Apache Doris, or similar technologies.
• Reliability, DR & Multi-Tenant Platforms
  • Design and operate platforms that remain resilient across node, service, zone, and infrastructure failures.
  • Implement and validate backup, recovery, disaster recovery, failover, and business-continuity capabilities.
  • Understand the fundamentals of multi-zone, multi-region, and active-active architectures and apply them where appropriate.
  • Build platforms that support multiple tenants and workloads, with appropriate isolation, scalability, resource management, and reliability.
  • Participate in DR exercises, failure simulations, migrations, and other resilience initiatives.
  • Understand distributed-system trade-offs involving replication, consistency, availability, partitioning, fault tolerance, latency, and throughput.
• Automation, Observability & Operations
  • Automate infrastructure and platform lifecycle operations using Terraform, Python, Bash, Go, or similar technologies.
  • Build reliable deployment and GitOps workflows and reduce manual operational effort.
  • Implement effective monitoring, logging, alerting, and observability for distributed workloads.
  • Participate in production incident response, root-cause analysis, and long-term reliability improvements.
• AI & Emerging Platform Infrastructure
  • Contribute to the infrastructure needed to support AI, machine-learning, and data-intensive workloads.
  • Help evolve cloud and Kubernetes platforms to support AI workloads, data pipelines, model-serving infrastructure, and associated platform services.
  • Understand the infrastructure requirements around compute, GPUs, networking, storage, data movement, observability, and workload isolation for AI platforms.
  • Work with engineering teams to build reusable platform capabilities that enable AI and data workloads to run reliably at scale.
  • Stay current with emerging infrastructure patterns across AI platforms, distributed data systems, and cloud-native technologies.

Qualifications

• 4–7 years of experience in Platform Engineering, Infrastructure Engineering, Distributed Systems, SRE, Backend Engineering, Data Infrastructure, or a related field.
• Strong production experience with Apache Kafka — mandatory.
• Hands-on production experience with Kubernetes — mandatory.
• Strong experience with at least one of MySQL or PostgreSQL — mandatory.
• Solid understanding of distributed-systems fundamentals including replication, partitioning, consistency, availability, fault tolerance, scalability, and failure recovery.
• Experience with ArgoCD/GitOps and infrastructure-as-code such as Terraform.
• Experience operating workloads on a public cloud such as GCP, OCI, AWS, or Azure.
• Strong production troubleshooting and incident-resolution skills.
• Experience with automation or scripting using Python, Bash, Go, Java, or similar languages.
• Understanding of high-availability, disaster-recovery, and multi-tenant architecture fundamentals.
• Experience with observability and operational tooling such as Prometheus, Grafana, OpenSearch/ELK, LGTM, or equivalent.
• Strong understanding of infrastructure and networking fundamentals in cloud-native environments.

Good to Have

• Experience with Kafka Connect, Debezium, Kafka Streams, or CDC platforms.
• Experience with distributed analytical databases such as StarRocks, ClickHouse, Apache Doris, or similar.
• Experience with Flink, Spark, or other distributed data-processing systems.
• Experience executing large-scale data, database, application, or infrastructure migrations.
• Experience with active-active, multi-zone, or multi-region systems.
• Experience operating stateful workloads on Kubernetes.
• Experience supporting AI/ML infrastructure or GPU-based workloads.
• Experience with cloud networking, service mesh, ingress, load balancing, or storage platforms.
• Contributions to Kubernetes, Kafka, distributed-systems, or other open-source infrastructure projects.

Benefits

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
• 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.
• 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.
• You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
• We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.