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Salary
$23k – $61k per year (Estimated)
Location
In office (Pune)
Seniority
Senior · 4+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Qualys, Inc. is a publicly traded enterprise cybersecurity, compliance, and IT solutions provider headquartered in Foster City, California. Founded in 1999 as a pioneer in SaaS-delivered vulnerability management, the company provides the Qualys Enterprise TruRisk Platform. Its single-agent cloud architecture unifies cybersecurity asset management, vulnerability management detection and response (VMDR), patch management, web application security, policy compliance, and cloud security across hybrid IT environments, public clouds, and containers.

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!

Job Summary

We are seeking a highly skilled and passionate Senior Software Engineer to join Qualys’ next-generation Platform & Middleware team who can take end-to-end ownership of software delivery-from design and development to validation, automation, release, and production reliability.

This role is ideal for engineers who enjoy building scalable backend systems while also owning quality through manual testing, automation, and release validation. Depending on project needs, the engineer may operate as a developer, SDET, or release owner to ensure successful delivery.

Responsibilities

  • Design and develop scalable backend services, platform components, and middleware systems using Java and related technologies.
  • Build reliable and maintainable APIs, distributed services, and cloud-native applications for large-scale SaaS environments.
  • Own features throughout the SDLC, including design, development, testing, automation, deployment, and support.
  • Perform functional, integration, and end-to-end validation of developed features.
  • Build and maintain automated test suites using PyTest and Playwright.
  • Contribute to architecture discussions, design reviews, performance optimization, scalability improvements, and reliability initiatives
  • Contribute to CI/CD pipelines, release validation, and deployment automation.
  • Troubleshoot complex distributed systems issues across services, databases, messaging systems, and cloud infrastructure
  • Improve system scalability, reliability, observability, and operational excellence.
  • Contribute to engineering best practices, coding standards, and technical mentorship within the team
  • Explore and adopt modern engineering productivity practices and tools where applicable.
  • Participate in code reviews, root cause analysis, and production support activities.

Required Skills

  • 4+ years of software development experience.
  • Strong Java programming skills and understanding of OOP, data structures, concurrency, and system design.
  • Experience building REST APIs, microservices, and distributed systems.
  • Experience writing unit, integration, and API-level automated tests as part of the development lifecycle
  • Familiarity with automation frameworks and validation tools such as PyTest , JUnit, Rest Assured, Playwright, Selenium, or similar technologies
  • Experience with Kafka, RabbitMQ, or similar messaging technologies.
  • Strong hands-on experience with Docker containers, Kubernetes, and CI/CD pipeline implementation and management.
  • Experience with container registries, including Docker Hub, OpenShift, and JFrog Artifactory.
  • Strong understanding of databases including SQL optimization and data modeling concepts
  • Exposure to NoSQL technologies such as Cassandra, MongoDB, or Redis
  • Strong debugging, troubleshooting, and problem-solving skills.
  • Good understanding of scalability, resiliency, observability, and production-grade system design

Preferred

Experience in SaaS, cloud security, or enterprise platforms.

Familiarity with AI-assisted development tools such as GitHub Copilot, Cursor, Windsurf, or Claude Code.

Exposure to performance engineering and observability tools

Nice to have: familiarity with emerging AI engineering concepts such as MCP integrations, agentic workflows, RAG pipelines, AI-powered developer tooling, or LLM-based automation

Understanding of SRE concepts and production reliability engineering

Education

Bachelor’s / Master’s degree in Computer Science, Engineering, or equivalent practical experience

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