Sr.staff software engineer network platform Jobs

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Staff Engineer - Performance Engineering

MontyCloud
Bengaluru, Karnataka

Quick apply

Job details

Qualifications

CI/CD
Computer Science
Kubernetes
NoSQL
Performance testing
Java
Master's degree
Databases
AWS
Analysis skills
Bachelor's degree
Distributed systems
Continuous integration
New Relic
Scripting
APIs
DynamoDB
SaaS
AI
Communication skills
Python

Full job description

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

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

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

Quick apply

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