Quick Heal Technologies Ltd. is India’s most trusted name in cybersecurity innovation. With a legacy of over 30 years, we’ve grown from a garage-born antivirus start-up to a globally respected, publicly listed cybersecurity product company with a market capitalisation of INR 2,500 Cr and revenues approaching INR 400 Cr.
Quick Heal has transformed from protecting individual users under the Quick Heal brand to safeguarding businesses of every size with our enterprise-grade Seqrite portfolio. Our mission - Innovate. Simplify. Secure. drives everything, we do.
We are home to India’s largest indigenous malware and threat research lab, and the creators of industry - first innovations like AntiFraud.ai and SiA, a Gen-AI powered analyst assistant. Our product stack spans Endpoint Protection, XDR, Zero Trust, Threat Intelligence, Data Privacy, and beyond - built upon a robust Cybersecurity Mesh Architecture.
Quick Heal Academy (QHA) is a leading institute for cybersecurity education and training. We collaborate with universities and organizations to build skilled professionals and strengthen the global cybersecurity ecosystem.
Quick Heal drives impactful CSR initiatives through its foundation, focusing on education, employability, vocational training, and cybersecurity awareness—contributing to a safer, inclusive, and sustainable future.
Position: Senior Software Engineer - Golang
Experience: 4 to 5 Years
Job Responsibilities:
- Design, develop, and maintain high-performance backend services using Golang
- Build and scale microservices-based architectures for enterprise security products
Must have skills:
- Experience with data stores – NoSQL (Redis, MongoDB, etc.)
- Strong proficiency in Golang
- Hands-on experience designing and developing microservices architectures
- Experience with data stores – NoSQL (Redis, MongoDB, etc.)
- Hands-on experience with messaging/streaming systems (Kafka, RabbitMQ, or similar)
- Familiarity with LLMs, vector databases
Good to have skills:
- Practical understanding of AI/ML concepts (supervised/unsupervised learning, model inference, feature engineering basics)
