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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer Cloud infrastructure - **Company:** Paramount Global - **Location:** Burbank, CA, United States - **Experience:** Expert - **Salary:** $124,000.0 - $186,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Automation of Tests, Batch Processing, Big Data, BigQuery, Cloud Computing, Cloud Engineering, Program Optimization, Software Quality, Information Engineering, Database Applications, Programming Tools, Disaster Recovery, Distributed Systems, Virtual Private Networks (VPN), Machine Learning, Peering, Prometheus, Software Construction, Software Engineering, Data Streaming, Data Logging, Load Balancing, Performance Testing, Feature Engineering, Spring Cloud, System Availability, Delivery Pipeline, Grafana, Multi-Cloud, Amazon Virtual Private Cloud (VPC), Build Management, Data Lakes, Kubernetes, Information Technology, Low Latency, Deployment Automation, Real Time Data, Apache Kafka, Terraform, Oracle Cloud Infrastructure, Dynatrace, Microservices - **Published:** July 24, 2026 - **Apply:** https://dejobs.org/x/x/3DE144D0B01A4C03861F90A2AC09170A/job/ ## About the Role This role requires deep expertise in distributed systems, cloud-native architecture, Kubernetes, and software engineering best practices. You should have a track record of operating at both the application and infrastructure layers., Streaming Optimization & Cloud Resource Utilization * Deep expertise in optimizing data streaming applications for throughput, latency, and cost-efficiency across cloud environments. * Proficient in tuning Kafka producers, consumers, and brokers including batch sizing, compression, partition strategies, and consumer lag management within cloud-hosted deployments. * Experience leveraging cloud-native managed services (e.g., Kafka, GCP Pub/Sub, BigQuery Streaming; OCI Streaming) to complement or extend Kafka-based pipelines. * Skilled at right-sizing and dynamically allocating cloud compute resources (VMs, node pools, spot/preemptible instances) to match streaming workload profiles and reduce infrastructure spend. * Familiarity with cloud-native autoscaling patterns for streaming consumers, including KEDA, HPA, and custom metrics-based scaling in Kubernetes. * Ability to identify and address performance bottlenecks at the intersection of application code and cloud resource limits * You should have experience benchmarking and profiling streaming pipelines from start to finish. You also need to turn your findings into improvements for infrastructure and code., This is a hybrid role. Candidates must have hands-on experience in both software engineering and cloud infrastructure. * 7+ years of experience in software engineering and cloud infrastructure, with at least 3+ years in each area. * Demonstrated expertise in optimizing data streaming applications on cloud infrastructure. * Proven track record building and operating production-grade real-time data platforms. * Experience mentoring engineers and collaborating across teams. * Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred. ## Description Optimize Data Streaming Applications on Cloud * Own end-to-end performance of data streaming applications running on cloud infrastructure from Kafka topic configuration through consumer processing and downstream delivery. * Profile and tune streaming pipelines to maximize throughput and minimize latency, leveraging cloud-native compute, storage, and networking resources. * Identify and address bottlenecks at the intersection of application code and cloud resource constraints, including CPU throttling, network saturation, I/O limits, and memory constraints. * Design and implement cloud resource utilization strategies. This includes spot/preemptible instances, managed streaming services, and dynamic node pool scaling to balance performance with cost efficiency. * Benchmark streaming pipelines end-to-end and translate findings into actionable infrastructure and code improvements. * Collaborate with Data and AI/ML engineering teams to ensure streaming pipelines are optimally provisioned for real-time feature engineering, inference, and analytics workloads. Design & Build Cloud-Native Applications * Develop high-throughput, low-latency streaming applications using Java and Kafka. * Design event-driven microservices that process, enrich, and route real-time data at scale. * Implement reactive, non-blocking architectures to support high concurrency and resilience. * Develop reusable streaming frameworks, libraries, and platform capabilities to improve engineering velocity and standardization. Architect & Operate Multi-Cloud Infrastructure * Architect, implement, and optimize multi-cloud infrastructure across GCP and OCI to support large-scale data and streaming workloads. * Design and implement advanced networking architectures, including VPC peering, VPNs, load balancers, and cross-region failover strategies. * Build and maintain Terraform-based infrastructure-as-code frameworks to standardize deployments and enable developer self-service. * Define autoscaling, deployment, failover, and resource optimization strategies for high-volume production systems. * Contribute to platform-wide architecture decisions related to scalability, resiliency, high availability, and disaster recovery. Kubernetes & Container Engineering * Deploy and manage containerized microservices within Kubernetes environments (GKE, OKE) across cloud platforms. * Implement container orchestration best practices, service-mesh configurations, and rolling-deployment strategies. * Partner with platform engineering teams to improve developer tooling, deployment automation, and runtime reliability. Production Reliability & Performance * Ensure production-grade reliability, observability, and operational maturity across streaming platforms and infrastructure. * Implement comprehensive observability using Prometheus, Grafana, centralized logging, distributed tracing, and health monitoring. * Optimize systems for throughput, latency, resiliency, resource efficiency, and cloud cost governance. * Build automated testing strategies for streaming and infrastructure workflows, including unit, integration, contract, chaos, and performance testing. * Lead incident response, root-cause analysis, and postmortems to improve uptime and reduce operational risk. Cross-Functional Collaboration * Partner with Data Engineering teams to integrate streaming architectures with batch processing, data lakes, and analytical platforms. * Collaborate with Software Engineering, Product Management, and API teams to enable real-time services and data-driven applications. * Work closely with AI/ML engineering teams to support real-time feature engineering, inference pipelines, and operational AI workload. * Clearly communicate technical tradeoffs to engineering stakeholders. Also, discuss scalability considerations and operational risks. Technical Management * Lead architectural discussions, design reviews, and technical deep dives across distributed systems and cloud infrastructure. * Drive engineering standards across code quality, documentation, observability, security, and platform maintainability. * Influence long-term technical strategy and modernization initiatives for real-time data infrastructure and cloud platforms. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Transforming Education: A Journey from interactive Markdown to Remote-Labs](https://www.wearedevelopers.com/videos/941-transforming-education-a-journey-from-interactive-markdown-to-remote-labs) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Inside Bitpanda's Tech Stack: Scaling a European Fintech Leader - Markus Dorner](https://www.wearedevelopers.com/videos/1979-inside-bitpanda-s-tech-stack-scaling-a-european-fintech-leader-markus-dorner) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [Best Countries for Software Engineers](https://www.wearedevelopers.com/magazine/267-best-countries-for-software-engineers)