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Java Selenium-Immediate joiner-Bangalore

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Onsite

Java Selenium-Immediate joiner-Bangalore

Tata Elxsi

Java Selenium-Immediate joiner-Bangalore

Skills

Google Cloud PlatformDockerPythonJavaC#GitLabJenkinsDatadogGrafanaSeleniumMachine LearningAIAWSAnsiblePrometheusGitHubLinuxKubernetesTerraformAzure

8 days ago

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Important information


Contract type:

Permanent

Salary:

₹500,000 – ₹1,100,000 / year

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

14 October 2026

What they need


Core Technical Skills

  • Strong automation engineering expertise using Selenium, JMeter, LoadRunner, Silk Test, UFT/QTP, TestComplete, Watir, Cucumber, or similar tools.
  • Hands-on programming experience with Python, Java, C++, or C# and development of API/UI automation frameworks.
  • Expertise in automation framework design, maintenance, extension, migration, and optimization.
  • Strong knowledge of SDLC, Agile/Lean/XP methodologies, CI/CD practices, software security, testing techniques, data structures, and algorithms.
  • Experience across unit, integration, system, functional, regression, exploratory, non-functional, performance, security, scalability, installability, migration, upgrade, and acceptance testing.
  • Linux/Windows scripting (Bash, PowerShell), networking fundamentals (TCP/IP, DNS, routing, firewalls, proxies, load balancing, packet analysis), and VMware administration-level expertise.
  • Experience validating Data Center, virtualized, hybrid, and cloud-hosted solutions.

AI-Enabled Quality Engineering

  • Practical use of AI coding assistants (GitHub Copilot, Claude, Cursor, or equivalent) to generate, refactor, and maintain automation frameworks while applying engineering judgment and code review.
  • Ability to generate deterministic, traceable, and verifiable test cases from requirements, user stories, specifications, APIs, and data models using AI.
  • Experience with AI-driven test design, coverage analysis, predictive test selection, flaky-test detection, automated triage, failure clustering, and regression optimization.
  • Hands-on knowledge of AI-enabled testing platforms, self-healing automation, visual AI validation, agentic testing, and associated risks.
  • Experience validating AI/ML systems including evaluation harnesses, statistical acceptance criteria, model regression testing, RAG validation, hallucination detection, guardrail verification, prompt injection, jailbreak testing, and OWASP LLM security practices.
  • Understanding of AI governance, evidential integrity, data privacy, tool validation requirements, and responsible use of AI in regulated environments.

Cloud & Modern Test Infrastructure

  • Experience containerizing test solutions with Docker and orchestrating execution on Kubernetes.
  • Infrastructure-as-Code and Environment-as-Code using Terraform, Ansible, ARM/Bicep, or CloudFormation.
  • CI/CD implementation using Jenkins, Azure DevOps, GitHub Actions, or GitLab CI.
  • Experience building ephemeral test environments, distributed test execution, and cloud-based test labs.
  • Strong knowledge of Azure, AWS, or Google Cloud, including compute, networking, identity, storage, databases, messaging, and security services.
  • Experience with observability platforms (Prometheus, Grafana, ELK/OpenSearch, Datadog, Application Insights, OpenTelemetry).
  • Expertise in performance engineering, resilience testing, chaos engineering, disaster recovery validation, cloud security testing, secrets management, and hybrid/cloud deployment validation.

Key Responsibilities

  • Derive test conditions from requirements and maintain end-to-end traceability from requirement to execution, defect, evidence, and closure.
  • Create and execute test strategies, plans, protocols, automation frameworks, and comprehensive V&V activities across functional and non-functional areas.
  • Drive quality throughout the SDLC, collaborating with development, product, architecture, and quality teams.
  • Build and maintain automation frameworks, test infrastructure, cloud environments, CI/CD pipelines, and quality metrics.
  • Validate AI-enabled products and services using approved tooling, evaluation frameworks, security testing, and governance controls.
  • Perform performance, resilience, security, scalability, cloud, hybrid, and edge deployment validation.
  • Produce objective evidence, V&V reports, release readiness assessments, and support audits and reviews.
  • Mentor junior engineers and contribute to quality engineering best practices and standards.

Preferred Qualifications

  • Experience with Proficy, Industrial Software, SCADA, MES, Historian, or other OT/Industrial platforms.
  • ISTQB Advanced Test Automation Engineer or Technical Test Analyst certification.
  • Azure, AWS, Kubernetes (CKA), VMware, AI/ML, or cloud-related certifications.
  • Experience with MLOps platforms, model registries, service virtualization, contract testing, security testing, accessibility validation, mobile automation, and SRE practices.

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