The Role
Leads organization-wide performance engineering for a cloud-native SaaS platform. Responsibilities include building self-service and AI-driven performance platforms, designing advanced tests for serverless and distributed systems, integrating testing into CI/CD, establishing benchmarks and service objectives, analyzing bottlenecks, monitoring production performance, capacity planning, optimizing cloud costs, and mentoring engineers. Requires extensive performance engineering experience, cloud and serverless expertise, programming skills, observability knowledge, and experience with AI/ML-based optimization.
Summary Generated by Built In
Role Overview
Key Responsibilities
We are seeking an experienced Lead Performance Test 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.
- 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
Must Have
- 8+ years of experience in performance engineering in large-scale SaaS or cloud-native environments
- Strong expertise in performance testing tools such as JMeter, Gatling, Locust, or similar
- Deep experience with serverless architectures (AWS Lambda, API Gateway, event-driven systems)
- Hands-on experience with performance monitoring and observability tools (CloudWatch, Datadog, New Relic, distributed tracing systems)
- Experience building performance engineering frameworks or platforms at scale
- Strong understanding of performance characteristics in distributed and serverless systems (latency, cold starts, concurrency, scaling behavior)
- Experience integrating performance engineering into CI/CD pipelines
- Proficiency in programming/scripting (Python, Java, or similar)
- Experience with AI/ML-based performance optimization techniques such as anomaly detection, predictive analysis, or adaptive load modeling
- Strong knowledge of cloud platforms (AWS preferred) and performance optimization techniques
- Proven ability to identify and resolve complex performance bottlenecks
- Experience with large-scale load testing and capacity planning
- Strong understanding of cost-performance trade-offs in cloud environments
Good To Have
- Experience with Kubernetes and containerized environments alongside serverless architectures
- Exposure to chaos engineering and resilience testing practices
- Experience building internal developer platforms or self-service tooling
- Knowledge of FinOps practices and cloud cost optimization strategies
- Experience with globally distributed or multi-region architectures
- Familiarity with API performance optimization techniques
- Experience with modern data stores (DynamoDB, Aurora Serverless, NoSQL systems)
- Exposure to 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
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- Equivalent practical experience in performance engineering or cloud-native systems
Skills Required
- 8+ years of experience in performance engineering in large-scale SaaS or cloud-native environments
- Strong expertise with JMeter, Gatling, Locust, or similar performance testing tools
- Deep experience with serverless architectures, including AWS Lambda, API Gateway, and event-driven systems
- Hands-on experience with CloudWatch, Datadog, New Relic, and distributed tracing systems
- Experience building performance engineering frameworks or platforms at scale
- Strong understanding of latency, cold starts, concurrency, and scaling behavior in distributed and serverless systems
- Experience integrating performance engineering into CI/CD pipelines
- Proficiency in Python, Java, or similar programming or scripting languages
- Experience with AI/ML-based performance optimization, anomaly detection, predictive analysis, or adaptive load modeling
- Strong knowledge of cloud platforms, preferably AWS, and performance optimization techniques
- Proven ability to identify and resolve complex performance bottlenecks
- Experience with large-scale load testing and capacity planning
- Strong understanding of cloud cost-performance trade-offs
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- Experience with Kubernetes and containerized environments
- Exposure to chaos engineering and resilience testing
- Experience building internal developer platforms or self-service tooling
- Knowledge of FinOps and cloud cost optimization strategies
- Experience with globally distributed or multi-region architectures
- Familiarity with API performance optimization
- Experience with DynamoDB, Aurora Serverless, or NoSQL systems
- Exposure to AIOps platforms and intelligent observability systems
MontyCloud Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about MontyCloud and has not been reviewed or approved by MontyCloud.
-
Fair & Transparent Compensation — Feedback suggests compensation and benefits are viewed favorably overall, indicating competitive pay positioning for many roles.
-
Healthcare Strength — Job postings indicate medical, dental, and vision coverage as part of a comprehensive package in the U.S.
-
Equity Value & Accessibility — Listings highlight equity participation as a standard component, signaling accessible ownership opportunities for employees.
MontyCloud Insights
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
MontyCloud is a Seattle, WA based intelligent Cloud Management Platform Company. Our customers use MontyCloud DAY2™ to instantly close the cloud skills gap, simplify CloudOps, and reduce the total cost of cloud operations up to 70%, all in just a few clicks. By leveraging the AWS public cloud, AI, and ML, DAY2 ™ simplifies provisioning, security, compliance, cost optimization, and routine operations. DAY2™’s automation first, No-Code approach helps customers immediately derive deep insights and deliver intelligent Cloud Operations in just a few minutes. You can try the platform for free at https://MontyCloud.com
.jpeg)
.jpg)
