Test Automation Engineer – AI Network & Observability Platform

About Us

Selector is building an operational intelligence platform for digital infrastructure. By adopting an AI/ML-based analytics approach, the platform provides actionable multi-dimensional insights to network, cloud, and application operators. It enables operations teams to meet their KPIs through seamless collaboration, search-driven conversational user experience, and automated data engineering pipelines.

Our solutions are used by leading Telecoms, Media Providers, Retail, and Professional Sports organizations across the world. Our novel approach and rapidly expanding footprint put us in the unique position for continued growth to become a category leader. To fuel our growth, we are seeking passionate, high-energy, results-oriented individuals to join our team.

Our mission is to deliver world-class solutions on behalf of the large enterprise. Supported by leading investors, Selector is uniquely positioned to deliver a world-class solution to address large enterprise requirements across the globe. 

Job Overview

We are looking for a highly skilled Test Automation Engineer to join our Engineering team. You will play a pivotal role in ensuring the reliability, performance, and scalability of our network observability solutions by designing, developing, and maintaining automated testing frameworks. You will collaborate closely with engineering, SRE, DevOps, Sales Customer Support teams to improve test coverage, accelerate delivery, and enhance product quality.

Key Responsibilities

• Design, develop, and maintain robust automated test frameworks and test suites for network and observability platforms.
• Define test strategies for functional, integration, performance, scalability, and regression testing.
• Collaborate with engineering teams to understand requirements, design test cases, and identify potential risks.
• Integrate automated tests into CI/CD pipelines to enable continuous testing and faster delivery cycles.
• Analyze test results, identify root causes of failures, and provide actionable feedback to development teams.
  
• Drive quality initiatives across the platform, including test coverage metrics, automation metrics, and reporting.
• Work with observability tools (logs, metrics, traces) to validate network behaviors and ensure platform reliability.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 2+ years of experience of hands-on experience in networking and load testing.
• Strong programming skills in languages such as Python, Java, or Go.
• Experience with test automation frameworks (e.g., Selenium/Playwright, Pytest, Robot Framework, JUnit).
• Preferred: Experience with network technologies, protocols (TCP/IP, BGP, SNMP), and observability tools (Prometheus, Grafana, ELK).
• Experience integrating tests with CI/CD pipelines (Jenkins, GitLab CI, or similar).
• Strong analytical, debugging, and problem-solving skills.
• Excellent communication skills and ability to influence quality practices across teams.

Preferred Qualifications

• Experience with large-scale distributed systems and cloud-native architectures.
• Knowledge of container orchestration (Kubernetes, Docker) and microservices testing.
• Familiarity with network performance testing and monitoring.
• Experience with test data management and simulation of network traffic.
  

Benefits & Perks

• Health Insurance (GMC): Comprehensive medical coverage for employees and dependents, including hospitalization and maternity benefits.
• Personal Accident Insurance (GPA): Coverage for accidental injury, both on and off duty.
• Life Insurance (Term Plan): Life insurance coverage for eligible employees.
• Provident Fund (PF): Company contribution as per statutory requirements.
• Gratuity: As per the Payment of Gratuity Act.
• Paid Time Off: Sick Leave, Earned Leave, and Maternity Leave in line with company policy and applicable laws.
• Holidays: National and regional holidays as per the annual holiday calendar.
• Final offer amounts are determined by multiple factors, including prior experience and location, and may vary from the amount listed.