Lead Subject Matter Expert
Qualys
- Location
- Pune
- Work model
- On-Site
- Level
- Senior
- Posted
- Jul 18, 2026
Skills
About this role
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
About Us
At Qualys , we are redefining how enterprises secure cloud-native applications, containers, AI workloads, and modern infrastructure at global scale. We are looking for an exceptional Senior Subject Matter Expert (SME) – Container, Cloud & AI Security Engineering to join our dynamic Product and SME organization. This is a highly strategic, hands-on individual contributor role for a passionate technologist who thrives at the intersection of cybersecurity, cloud, containers, DevSecOps, and emerging AI technologies. As a trusted advisor, evangelist, and technical leader, you will help shape the future of Qualys Cloud, Container, and AI Security solutions, enabling thousands of enterprise customers worldwide to securely adopt modern architectures, AI-powered applications, LLMs, agentic workflows, and cloud-native technologies. If you are a tech-savvy storyteller with deep technical expertise, customer-facing excellence, and a passion for innovation in cloud, container, and AI security, we want to hear from you.
Responsibilities
As a seasoned SME, you will serve as a strategic technical leader focused on customer enablement, sales acceleration, product evangelism, and real-world adoption of Qualys Cloud, Container, and AI Security solutions. Your expertise across cloud-native security, Kubernetes ecosystems, DevSecOps, application security, AI/LLM security, and modern infrastructure platforms will be instrumental in driving customer success and influencing product direction.
Key Responsibilities
Subject Matter Expertise: Demonstrate deep expertise in Container Security, Cloud Security, Kubernetes, DevSecOps, AI/LLM Security, and modern application architectures. Customer Enablement: Act as the voice of the customer by delivering value-driven demos, architectural guidance, deployment best practices, and strategic security recommendations for cloud-native and AI-powered environments. AI & Emerging Technology Leadership: Advise customers and internal teams on securing AI applications, LLM deployments, Model Context Protocol (MCP) services, agentic AI workflows, AI supply chains, and modern AI infrastructure. Technical Support & Escalations: Partner closely with engineering, product management, support, and operations teams to troubleshoot complex deployment, integration, and design challenges across cloud, container, and AI environments. Sales & Field Enablement: Support the sales organization with technical positioning, RFP/RFI responses, customer workshops, beta programs, proof-of-concepts (POCs), and strategic engagements. Content Development: Create impactful technical content including solution briefs, feature blogs, architecture guidance, demo videos, best-practice documentation, competitive positioning, and thought leadership material focused on cloud-native and AI security. Training & Evangelism: Deliver high-quality enablement sessions, technical workshops, partner training, webinars, and field updates on emerging technologies, product capabilities, AI security trends, and competitive differentiation. Competitive Intelligence: Analyze market trends and competitor offerings across Cloud Security, CNAPP, CSPM, CWPP, AI Security, and runtime protection technologies to strengthen Qualys positioning. Product & Marketing Collaboration: Work closely with product management and product marketing teams to influence roadmap direction, improve customer adoption, and create compelling technical demonstrations and collateral.
Qualifications
Experience 5+ years of experience in Solution Engineering, Pre-Sales Engineering, Technical Product Evangelism, Security Architecture, or related customer-facing security roles. Strong background in Cloud Security, Container Security, DevSecOps, or Application Security platforms. Experience with AI/LLM technologies, AI security, or securing modern AI application ecosystems