Job Title: Senior Runtime Performance Specialist Location: UAE (Remote)
Employment Type: Full-Time
Level: Senior
Work Arrangement: Fully Remote — 100% Work From Home
About Us We are committed to delivering high-performance, reliable, and scalable software systems through advanced runtime optimization, performance engineering, and continuous technical improvement. We are seeking an experienced Senior Runtime Performance Specialist to analyze application runtime behavior, identify performance bottlenecks, optimize resource utilization, and improve the responsiveness, stability, and efficiency of software applications and infrastructure.
The successful candidate will possess strong expertise in runtime diagnostics, performance profiling, memory management, concurrency, system architecture, and application optimization. This role involves collaborating remotely with software engineers, platform teams, DevOps specialists, and technical architects to ensure applications operate efficiently under varying workloads and production conditions.
Key Responsibilities - Analyze application runtime behavior to identify performance bottlenecks, excessive resource consumption, latency issues, and execution inefficiencies.
- Conduct comprehensive performance profiling across application code, runtime environments, operating systems, virtual machines, and supporting infrastructure.
- Optimize CPU utilization, memory allocation, garbage collection, thread scheduling, concurrency, and other runtime characteristics.
- Investigate application latency, throughput limitations, resource contention, deadlocks, race conditions, and unexpected runtime failures.
- Develop and execute performance benchmarks, load tests, stress tests, and scalability assessments to evaluate application behavior under different workload conditions.
- Analyze runtime metrics, execution traces, profiling data, logs, and system telemetry to determine the root causes of performance degradation.
- Optimize application execution paths, algorithms, data structures, memory access patterns, and resource management strategies.
- Evaluate runtime environments such as Java Virtual Machine (JVM), .NET CLR, Node.js, Python, or other relevant execution platforms based on the organization's technology stack.
- Review garbage collection behavior, heap utilization, memory leaks, object allocation patterns, and memory fragmentation where applicable.
- Assess the performance impact of application frameworks, third‑party libraries, runtime configuration settings, and software dependencies.
- Collaborate with development teams to review code, recommend optimization techniques, and implement performance improvements.
- Establish performance baselines, service‑level objectives, capacity thresholds, and runtime health indicators for critical applications.
- Investigate production performance incidents, conduct root‑cause analyses, and recommend corrective and preventive actions.
- Support capacity planning by analyzing workload patterns, resource consumption trends, traffic projections, and expected application growth.
- Evaluate the performance implications of software upgrades, runtime version changes, infrastructure modifications, and architectural decisions.
- Improve application startup time, execution efficiency, response time, throughput, and resource utilization.
- Design repeatable performance testing procedures and integrate automated performance checks into continuous integration and continuous delivery pipelines.
- Develop scripts and utilities to automate profiling, benchmarking, diagnostic analysis, and performance regression detection.
- Monitor runtime performance across development, testing, staging, and production environments to ensure consistent operational standards.
- Establish and maintain technical documentation covering performance findings, optimization recommendations, benchmarking methodologies, and runtime configuration guidelines.
- Work with cloud engineering and platform teams to optimize containerized applications, virtual machines, and cloud‑hosted workloads.
- Evaluate observability tools, application performance monitoring platforms, distributed tracing systems, and profiling solutions.
- Recommend architectural improvements when performance issues originate from inefficient service communication, database access, caching strategies, or distributed processing.
- Mentor engineering colleagues on performance engineering techniques, profiling methodologies, runtime behavior, and optimization best practices.
- Maintain awareness of emerging runtime technologies, compiler optimizations, performance analysis techniques, and software engineering standards.
- Perform all responsibilities remotely using secure development environments, monitoring platforms, version control systems, and digital collaboration tools.
Qualifications and Experience - Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical discipline.
- A master's degree in Computer Science, Systems Engineering, or Performance Engineering is an advantage.
- At least 5–8 years of experience in software engineering, performance engineering, runtime optimization, systems development, or application diagnostics.
- Demonstrated experience profiling and optimizing complex applications in production or performance‑critical environments.
- Strong understanding of runtime execution models, memory management, garbage collection, concurrency, threading, and process scheduling.
- Experience with at least one major runtime ecosystem, such as Java/JVM, .NET CLR, Node.js, Python, Go, or another relevant application platform.
- Proficiency in one or more programming languages used for performance‑sensitive applications, such as Java, C++, C#, Go, Rust, or Python.
- Experience using profiling and diagnostic tools to investigate CPU hotspots, memory leaks, thread contention, latency, and resource utilization.
- Strong knowledge of operating system fundamentals, including processes, threads, virtual memory, file systems, networking, and system resource management.
- Experience with performance benchmarking, load testing, stress testing, and performance regression analysis.
- Familiarity with distributed systems, microservices, containerized workloads, and cloud‑native application architectures.
- Knowledge of application performance monitoring, distributed tracing, centralized logging, and metrics‑based observability.
- Experience with tools such as profilers, debuggers, benchmarking frameworks, and performance monitoring platforms relevant to the chosen technology stack.
- Understanding of caching strategies, database query performance, network latency, serialization overhead, and inter‑service communication.
- Familiarity with CI/CD pipelines and automated testing frameworks for integrating performance checks into software delivery workflows.
- Ability to interpret complex performance data and translate findings into practical engineering improvements.
- Strong analytical, troubleshooting, problem‑solving, and technical decision‑making skills.
- Excellent written and verbal communication skills, including the ability to explain performance findings to technical and nontechnical stakeholders.
- Experience preparing technical reports, documenting optimization strategies, and presenting measurable performance improvements.
- Ability to manage multiple investigations, prioritize high‑impact issues, and work independently in a fully remote environment.
- High standards of code quality, technical accuracy, security awareness, and engineering discipline.
Key Performance Indicators (KPIs) - Application Response Time: Improve response times and reduce latency across critical application workflows.
- Runtime Efficiency: Reduce unnecessary CPU consumption, memory usage, and runtime overhead.
- Throughput Improvement: Increase application processing capacity without compromising reliability or correctness.
- Performance Stability: Minimize performance degradation, resource exhaustion, and runtime‑related incidents.
- Memory Optimization: Identify and resolve memory leaks, excessive allocations, and inefficient memory utilization.
- Scalability: Improve application performance under increasing workloads and concurrent user activity.
- Incident Resolution: Diagnose and resolve runtime performance issues within agreed service‑level targets.
- Regression Prevention: Reduce performance regressions through automated benchmarks and continuous monitoring.
- Optimization Delivery: Implement measurable improvements against established performance baselines.
- Diagnostic Accuracy: Identify root causes efficiently and provide evidence‑based recommendations.
- Documentation Quality: Maintain clear performance reports, reproducible benchmarks, and reliable technical documentation.
- Engineering Collaboration: Support development and platform teams in adopting effective performance optimization practices.
What We Offer - Competitive compensation based on qualifications, experience, and technical expertise.
- 100% fully remote work arrangement , with no routine office attendance required.
- Opportunities to solve challenging runtime performance problems across modern software systems.
- Exposure to advanced profiling tools, performance engineering practices, cloud platforms, and distributed architectures.
- A collaborative engineering environment that values technical excellence, measurable improvements, and continuous learning.
- Opportunities for professional development and career advancement in performance engineering and systems optimization.
- Access to digital collaboration tools and secure technical environments that support effective remote work.
- A performance‑oriented culture focused on software quality, system reliability, scalability, and operational efficiency.
#J-18808-Ljbffr