MontyCloud

Role Overview

We are seeking an experienced Staff Performance Engineer to lead and scale performance engineering practices for our cloud-native SaaS platform. This role is responsible for driving performance, scalability, reliability, and cost efficiency at an organizational level, with a strong focus on serverless and distributed architectures.

You will define performance engineering strategy, build scalable and AI-driven performance platforms, and influence architectural decisions across teams. The role requires deep expertise in modern cloud environments and a strong focus on embedding performance into the entire software lifecycle, from development to production.


Key Responsibilities

  • Define and drive organization-wide performance engineering strategy aligned with business KPIs, customer experience, and cost efficiency
  • Architect and build scalable, self-service performance engineering platforms enabling teams to run performance tests and analysis independently
  • Design and implement AI-driven performance engineering solutions including anomaly detection, predictive performance insights, adaptive load testing, and automated optimization recommendations
  • Lead the design and execution of advanced performance testing strategies for serverless, distributed, and event-driven systems
  • Establish and standardize performance benchmarks, SLAs, SLOs, and KPIs across services
  • Drive integration of performance testing and validation into CI/CD pipelines to enable continuous performance engineering (shift-left approach)
  • Analyze system-wide performance bottlenecks including latency, cold starts, concurrency limits, and resource utilization across distributed systems
  • Collaborate with engineering, SRE, and architecture teams to influence system design for scalability, resilience, and performance optimization
  • Own performance in production environments by leveraging observability tools, distributed tracing, and real-time monitoring systems
  • Implement intelligent observability solutions using tools such as CloudWatch, Datadog, New Relic, and AI-based monitoring platforms
  • Lead capacity planning and scalability initiatives for high-throughput and globally distributed systems
  • Drive cost-performance optimization strategies in cloud-native environments (FinOps alignment)
  • Mentor and guide engineers across teams, promoting a performance-first culture and best practices
  • Stay updated with emerging trends in performance engineering, including AI/ML-driven optimization and cloud-native innovations


Desired Skill and Requirements


Must Have

  • 8+ years of experience in performance engineering within large-scale SaaS or cloud-native environments
  • Performance testing tools - JMeter, Gatling, Locust, or similar
  • Serverless architectures - AWS Lambda, API Gateway, event-driven systems
  • Performance monitoring and observability tools - CloudWatch, Datadog, New Relic, distributed tracing systems
  • Building performance engineering frameworks or platforms at scale
  • Performance optimization in distributed and serverless systems - latency, cold starts, concurrency, and scaling behavior
  • Integration of performance engineering into CI/CD pipelines
  • Programming/scripting - Python (preferred), Java, or similar
  • AI/ML-based performance optimization techniques - anomaly detection, predictive analysis, adaptive load modeling
  • Cloud platforms (AWS preferred) and performance optimization techniques
  • Ability to identify and resolve complex performance bottlenecks
  • Large-scale load testing and capacity planning
  • Cost-performance optimization in cloud environments


Good To Have

  • Kubernetes, containerized, and serverless architectures
  • Chaos engineering and resilience testing
  • Internal developer platforms and self-service tooling
  • FinOps and cloud cost optimization strategies
  • Globally distributed and multi-region architectures
  • API performance optimization
  • Modern distributed data stores - DynamoDB, Aurora Serverless, NoSQL systems
  • AIOps platforms and intelligent observability systems


Soft Skills

  • Strong problem-solving and analytical thinking
  • Ability to influence architectural and technical decisions across teams
  • Excellent communication and stakeholder management skills
  • Ownership mindset with the ability to drive cross-functional initiatives
  • Mentorship and leadership capabilities
  • Ability to operate in a fast-paced, high-growth SaaS environment


Experience

  • 8+ years of experience in performance engineering in large-scale SaaS or cloud-native environments
  • 3+ years of experience in Senior, Lead, or Staff-level performance engineering roles
  • 4+ years of experience performance testing large-scale SaaS or distributed systems
  • 5+ years of hands-on experience with performance testing tools such as JMeter, Gatling, k6, or Locust
  • Experience designing and executing large-scale performance tests in production-like environments
  • Experience identifying and resolving performance bottlenecks across application, database, network, and infrastructure layers
  • Experience tuning databases for performance at scale
  • Experience defining and implementing performance benchmarks, KPIs, and capacity planning strategies
  • Experience working with observability and monitoring platforms for performance analysis
  • Experience optimizing event-driven and serverless architectures
  • Experience influencing architecture and engineering decisions across teams and domains
  • Experience operating in fast-paced, high-growth SaaS environments


Education

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
  • Equivalent practical experience in performance engineering or cloud-native systems
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