Lead Performance Engineer

Greetings From NAM INFO Pvt

Performance Engineer III

Experience: 6–8 Years

Location: Siruseri – EB6 / Gitanjali Park – SEZ

Job Summary

We are looking for an experienced Performance Engineer to work on large-scale distributed systems and cloud platforms in a high-traffic e-commerce environment. The role involves performance testing, monitoring, troubleshooting, and tuning applications to improve scalability, reliability, and overall system performance.

Key Responsibilities

• Design and execute performance testing strategies including load, stress, and capacity testing.
• Use tools such as JMeter, Locust, or LoadRunner for performance testing.
• Automate performance tests as part of CI/CD pipelines.
• Analyze performance issues using thread dumps, heap dumps, and TCP dumps.
• Monitor applications using APM tools such as New Relic or Dynatrace.
• Use Splunk for log analysis, dashboards, queries, alerts, and root-cause analysis.
• Tune application servers such as Tomcat, Node.js, and Spring Boot.
• Analyze network performance using tools such as Wireshark, ExtraHop, and Riverbed.
• Monitor systems and proactively identify performance bottlenecks.
• Analyze browser performance using Lighthouse, Chrome DevTools, Catchpoint, and WebPageTest.
• Work closely with Developers, SRE, QA, and DevOps teams.
• Participate in code reviews and ensure performance best practices are followed.

Required Skills

• 6–8 years of experience in Performance Engineering / Performance Testing.
• Strong hands-on experience with JMeter is preferred.
• Experience with Splunk for log analysis and troubleshooting.
• Strong knowledge of APM tools such as New Relic or Dynatrace.
• Experience with performance test planning, execution, analysis, reporting, and defect tracking.
• Good understanding of microservices architecture.
• Experience with performance tuning of Tomcat, Node.js, and Spring Boot.
• Strong troubleshooting and root-cause analysis skills.
• Good understanding of CI/CD and performance test automation.

Good to Have

• Programming experience in Java, Python, or Groovy.
• Experience analyzing heap dumps, thread dumps, and TCP dumps.
• Knowledge of Wireshark or CloudShark.
• Experience with Fiddler and Chrome DevTools.
• Knowledge of Azure, AKS, or GCP.
• Certifications in Azure, Splunk, or New Relic.

Required Skills

* Strong hands-on experience with any one of the following performance testing tools (mandatory): IBM Rational Performance Tester (RPT) (Preferable), LoadRunner, Apache JMeter.

* Proven capability to establish and run Performance Engineering cycles independently.

* Solid understanding of API performance & microservices, distributed systems & high-throughput transaction platforms.

* Strong fundamentals in SQL basics & database performance.

* Experience with Linux OS performance metrics and system-level analysis.

* Ability to interpret APM/log insights and translate them into actionable tuning recommendations.

Job Summary

We are looking for a QA Automation Engineer with strong experience in performance testing using JMeter, Groovy, and Java, along with knowledge of automation frameworks and API testing.

Mandatory Skills

• Hands-on experience with Apache JMeter, Groovy, and Java for performance and load testing.
• Experience in API, integration, and end-to-end testing.
• Knowledge of automation framework design and debugging.
• Experience with AWS, CI/CD pipelines, and test reliability.
• Strong analytical, reasoning, and problem-solving skills.

Preferred Skills

• Experience with Go (Golang) programming and Ginkgo testing framework.
• Experience testing cloud-hosted applications and troubleshooting using logs and monitoring.

Immediate Hiring | QA Automation Engineer

📍 Location: Bangalore

💼Experience: 5 Years

We are looking for a strong QA Automation Engineer with hands-on experience in Groovy, Java and JMeter, along with a solid understanding of automation framework design, API testing and cloud-based applications.

Key Skills Required

• QA Automation & Framework Design

• Groovy + Java for automation testing

• JMeter – Performance Testing

• Go / Golang, Ginkgo – preferred

• API Integration Testing

• AWS – practical experience

• CI/CD amp; Test Automation Pipelines

• Debugging, failure investigation, flaky test analysis

• Strong aptitude, reasoning and problem-solving skills

What We’re Looking For

✔ Ability to design and maintain reusable automation frameworks

✔ Strong understanding of API, integration and end-to-end testing

✔ Experience designing performance workloads and analyzing JMeter results

✔ Ability to troubleshoot using AWS logs and monitoring

✔ Good understanding of test reliability and CI/CD environments

✔ Someone who can independently identify edge cases and investigate failures

Navtech is looking for a Performance Engineer to characterize, benchmark, and optimize application workloads across CPU and GPU architectures — in bare-metal, virtualized, and distributed/cluster environments. You'll work with cross-functional teams to identify software bottlenecks and drive performance improvements.

Working as a Performance Engineer at Navtech, you will:

• Benchmark and profile workloads on CPU/GPU architectures using tracing tools like VTune and Linux Perf.
• Analyze performance data to identify software bottlenecks and recommend optimizations.
• Tune applications running in cluster and distributed environments.
• Build performance monitoring scripts and automation using C, C++, and Python.
• Apply knowledge of server ecosystem components (memory, storage, networking), virtualization, and Linux internals to performance tuning.
• Document benchmarks and optimization findings for engineering and client stakeholders.
• 
  

Who Are We Looking For Exactly?

• 2+ years of experience in bare-metal and virtual machine environments, with 2+ years of software development in C, C++, and Python.
• Hands-on experience with benchmarking, tracing tools, VTune, and Linux Perf.
• Working knowledge of server architecture, virtualization, and Linux OS internals.
• Experience with distributed/cluster application environments.
• Exposure to simulation technologies (functional, cycle-accurate/timing, performance) and profile-guided optimization is a plus.
• Strong problem-solving, communication, and documentation skills.
• B.S./M.S. in Computer Engineering, Computer Science, or related field.

Key Responsibilities

• Design, deploy, configure, upgrade, and administer enterprise-scale Dynatrace environments.
• Deploy and manage OneAgent, ActiveGate, extensions, and monitoring configurations across application and infrastructure environments.
• Implement observability for applications, APIs, microservices, databases, containers, Kubernetes, cloud platforms, and traditional infrastructure.
• Configure service detection, process groups, management zones, tags, naming rules, metrics, logs, traces, and topology.
• Develop operational and executive dashboards, notebooks, reports, SLOs, and alerting strategies.
• Configure and optimize Davis AI problem detection, anomaly detection, baselines, and root-cause analysis.
• Implement Real User Monitoring (RUM), Synthetic Monitoring, Session Replay, distributed tracing, and log monitoring as required.
• Analyze application performance issues, service dependencies, transaction traces, response times, resource utilization, and infrastructure bottlenecks.
• Lead troubleshooting of complex production performance and availability incidents using Dynatrace telemetry.
• Reduce alert noise through effective event correlation, thresholds, anomaly-detection configuration, and monitoring standards.
• Integrate Dynatrace with enterprise platforms such as ServiceNow, Jira, PagerDuty, Splunk, CI/CD pipelines, and collaboration/notification tools.
• Automate Dynatrace configuration and deployment using APIs, configuration-as-code, scripting, and DevOps tooling.
• Work closely with application, infrastructure, cloud, SRE, DevOps, production support, and operations teams to define observability requirements.
• Establish Dynatrace monitoring standards, reusable configurations, governance, and best practices.
• Perform platform health checks, capacity assessments, license/usage optimization, and monitoring coverage reviews.
• Create technical documentation, runbooks, architecture diagrams, troubleshooting guides, and operational procedures.
• Mentor junior engineers and provide technical leadership for observability initiatives.

Required Technical Skills

• 5–8+ years of overall IT experience with significant experience in application/infrastructure monitoring or observability.
• 3–5+ years of hands-on Dynatrace experience in enterprise environments.
• Strong knowledge of:
• Dynatrace OneAgent and ActiveGate
• Application Performance Monitoring (APM)
• Infrastructure Monitoring
• Distributed Tracing
• Real User Monitoring (RUM)
• Synthetic Monitoring
• Log Monitoring and Analytics
• Metrics, traces, logs, and events
• Davis AI and automated root-cause analysis
• Dashboards, SLOs, alerting, and anomaly detection
• Dynatrace APIs and automation
• Experience monitoring Java/JVM, .NET, web applications, APIs, microservices, and databases.
• Experience with Kubernetes, Docker, OpenShift, or other container platforms.
• Working knowledge of at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
• Strong understanding of application architecture, HTTP/HTTPS, REST APIs, networking, operating systems, and middleware.
• Experience with Linux and Windows environments.
• Scripting/automation experience using Python, PowerShell, Bash, Ansible, Terraform, or similar technologies.
• Experience integrating monitoring platforms with ITSM, incident management, and DevOps tools.
• Strong analytical and production troubleshooting skills.

Preferred Skills

• Experience with Dynatrace Grail, DQL (Dynatrace Query Language), OpenPipeline, and the latest Dynatrace platform capabilities.
• Knowledge of OpenTelemetry (OTel) and modern telemetry standards.
• Experience implementing observability for large-scale Kubernetes and cloud-native environments.
• Familiarity with SRE practices, including SLIs, SLOs, error budgets, and observability-driven incident management.
• Knowledge of additional monitoring platforms such as Splunk, AppDynamics, Datadog, New Relic, Grafana, Prometheus, or ELK.
• Experience with infrastructure-as-code and configuration-as-code approaches.
• Dynatrace certifications are preferred.

Professional Skills

• Strong problem-solving and root-cause analysis capabilities.
• Ability to troubleshoot complex application and infrastructure performance issues independently.
• Strong written and verbal communication skills.
• Ability to work effectively with application owners, developers, SREs, infrastructure teams, and senior stakeholders.
• Ability to translate business and operational requirements into observability solutions.
• Experience working in enterprise production environments with incident, problem, and change-management processes.
• Ability to mentor engineers and drive technical standards across teams.

Education & Certification

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent professional experience.
• Dynatrace Associate/Professional-level certification is desirable.
• Cloud, Kubernetes, ITIL, SRE, or DevOps certifications are advantageous.

Experience Level

Senior Engineer

• Overall Experience: 5–8+ years
• Dynatrace/Observability Experience: 3–5+ years
• Expected proficiency: Advanced hands-on implementation, administration, troubleshooting, automation, and solution design

About the team

SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.

About the Role

We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.

You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.

What You’ll Do

●    Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.

●    Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.

●    Performing functional, regression, performance, scalability and security testing to identify bugs or defects.

●    Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.

●    Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.

●    Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.

●    Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.

●    Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.

●    Ensuring the software meets customer and business requirements by validating the functionality and performance.

●    Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.

●    Supporting user acceptance testing (UAT) and assisting clients with product validation.

●    Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.

Required Experience

●    A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.

●    8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.

●    Expertise in manual and automated testing.

●    Deep domain expertise in complex system validation and advanced automation practices at scale.

●    Proficiency in programming languages like Python to build and run automated test scripts.

●    "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."

●    Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.

●    Strong communication skills for documenting test results and interacting with cross-functional teams.

●    Excellent analytical skills, attention to detail, and problem-solving ability.

●    Ability to work independently as well as collaboratively in a team environment.

●    A curious mindset with a willingness to quickly learn new technologies and testing tools.

Required Skills & Qualifications

●    Familiarity with cloud-based testing environments (GCP, AWS, Azure).

●    Experience with cybersecurity products or cloud services or IDP or Web UI

The Mindset

●    Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.

●    Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.

●    Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.

●    Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.

Position Overview 

The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems. 

Responsibilities 

• Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms 
• Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning 
• Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection 
• Deploy, maintain and monitor containerized ML workloads 
• Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows 
• Implement AI-driven data validation, schema and concept drift detection and metadata management. 
• Establish governance frameworks for AI systems, including bias detection, explainability, and auditability 
• Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention 
• Develop automated test suites for model performance, regression, edge cases and bias validation 
• Monitor model KPIs (accuracy, precision, recall, latency, calibration) 
• Ensure reproducability of experiments and production models 
• Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption 

Qualifications 

• Bachelor’s degree in computer science, Data Science, Information Systems, or a related field 
• 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering 
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure 
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn 

Very strong infra engineer to administer Linux based VMs (and few Windows VMs as well).

Must have strong knowledge and hands-on on docker, Kubernetes

Must be good at monitoring (AppDynamics, Prometheus, Grafana) and logging (Splunk)

Develop automation scripts using Shell and Python. Must have good knowledge in Ansible.

Should be good at optimize/finetune server configurations.

 Should be good in troubleshoot issues and fix them.

• 12 - 16 years of experience in Enterprise Software Product Engineering (Development/Quality) 
• Working experience with Enterprise SaaS product companies 
• 6+ years of experience in leading/managing multi-discipline activities - manual, automation, performance and security testing. 
• Experience with AI powered test automation frameworks like Playwright, TestRigor etc is preferable. 
• Experience with security and performance testing tools like BurpSuite, Locust, K6 etc   
• Strong experience in generating and presenting data/metric driven reports to exec/C-level stakeholders. 
• Self drive to achieve team and organization goals with high ROI 
• Result oriented collaborator and enabler of success. 
• Preferred: 
• Enterprise software experience withing the Life Sciences industry and good understanding of GxP requirements 
• Knowledge of cloud native, distributed architecture 

Responsibilities:

• Lead the overall strategy, execution, reporting of ValGenesis’s platform/integration testing activities 
• Own the strategic vision and establish the Software QA processes, tools, frameworks. Ensure, Monitor and Measure of the same in terms of rollout, adoption, results. 
• Change advocate of lean and efficient working – Processes, Tools, Resources. 
• Work with the engineering and cross-functional leaders along with the developers/testers to achieve continuous and incremental quality improvement across all products. 
• Own and deliver automation, security, performance testing frameworks/tools/strategies.  
• Enable the adoption of such tools/frameworks during development phase. 
• Build tools to monitor and generate metrics of all QA activities - test definition, execution, results, production incidents etc. 
• Build a strategy and deliver capabilities to fully automate computer software validation for all product releases. 
• Build and sustain high performance teams – Hiring, Performance and Talent Management