At TrueLark, our infrastructure powers mission-critical business applications for customers across industries. As we continue to grow, we need a Scaling Engineer who can design and implement scalable, high-performance infrastructure solutions.
You will focus on optimizing performance, improving system resilience, and scaling our services built on Redis, MySQL, ActiveMQ, and Jetty Spark servers. This is a highly impactful role where you will collaborate with engineering and DevOps teams to ensure our systems perform reliably under heavy load.
This position will be (remote, in office, hybrid (remote/in office))
Reports to: Head of TrueLark Technology
Infrastructure Scaling & Optimization: Analyze current infrastructure and design solutions to handle increasing load with high availability.
Database Performance Tuning: Optimize MySQL (indexes, queries, partitioning, replication, sharding) and Redis caching strategies for throughput and latency improvements.
Message Queue Scaling: Enhance and optimize ActiveMQ for large-scale, distributed messaging with high durability and reliability.
Server & Application Scaling: Tune Jetty Spark servers for concurrency, session management, load balancing, and failover strategies.
Monitoring & Bottleneck Detection: Implement monitoring dashboards (Grafana, Prometheus, ELK/EFK, or Azure Monitor) to detect slow queries, CPU/memory bottlenecks, and scaling issues.
Distributed Systems Reliability: Ensure fault tolerance, disaster recovery, and horizontal scaling strategies.
CI/CD & Automation: Work with GitHub Actions, Jenkins, or Azure DevOps for automated deployments and scaling workflows.
Collaboration: Partner with backend engineers, DevOps, and product teams to deliver reliable infrastructure that meets performance goals.
Bachelor’s degree in Computer Science, Information Technology, or related field.
3+ years of experience in scaling infrastructure for distributed systems or high-traffic applications.
Strong hands-on experience with:
Databases: MySQL (query optimization, replication, partitioning, indexing strategies).
Caching: Redis (cluster setup, pub/sub, eviction policies, memory optimization).
Message Queues: ActiveMQ (scaling consumers/producers, HA clusters, performance tuning).
Web Servers: Jetty with Spark framework (thread pools, tuning JVM, load balancing).
Proficiency in monitoring & observability tools (Grafana, Prometheus, ELK/EFK stack, Azure Monitor, or DataDog).
Knowledge of distributed systems principles (CAP theorem, sharding, replication, consensus).
Familiarity with CI/CD pipelines, Docker, Kubernetes (AKS/EKS/GKE optional).
Strong problem-solving skills in debugging production performance bottlenecks.
Ability to work independently and collaboratively in a fast-paced environment.
Experience with horizontal scaling of microservices in production.
Knowledge of cloud platforms (Azure, AWS, GCP) for scaling and infrastructure automation.
Hands-on experience with load testing tools (JMeter, Locust, k6, Artillery).
Familiarity with event-driven architecture and streaming platforms (Kafka).
Contributions to open-source performance/scaling projects
Weave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know.
All official correspondence will occur through Weave branded email. We will never ask you to share bank account information, cash a check from us, or purchase software or equipment as part of your interview or hiring process.
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