Sr. Staff Engineer Software, Full Stack - NetSec - Bangalore

Job description

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary The Team Public Cloud (Prisma) - As the leader of the Public Cloud Security team, you will be responsible for building products that protect data, workloads, and infrastructure for some of the largest enterprise customers in the world. We help the customers in their transitional journey to the cloud by ensuring they have the best-in-class protection. The cloud market has been growing at a rapid rate for the last few years. As more and more enterprises use public cloud, there is an insatiable demand for securing workloads in the public cloud. With our recent acquisition of Prisma Public Cloud, formerly RedLock™, and Evident.io, Palo Alto Networks is the reigning market leader. Job Summary Join our team building a cutting-edge multi-tenanted GenAI Security Platform that helps organisations validate and secure their AI systems against adversarial attacks. Key Responsibilities • Design and implement high-performance REST APIs with enterprise-grade multi-tenant isolation and strict security boundaries. • Work on distributed systems architecture handling high-throughput workloads with mission-critical uptime requirements. • Build responsive dashboards and administrative interfaces for platform management, data visualisation, and system configuration. • Integrate multiple LLM providers, implement semantic search capabilities, and build intelligent agent workflows. • Architect complex, multi-step AI evaluation pipelines for asynchronous job execution and large-scale data processing. • Design and implement database schemas with proper indexing, query optimisation, and data isolation strategies. • Build and maintain scalable micro-services with async/await patterns and type-safe code. • Develop data-intensive UIs with real-time updates, complex state management, and intuitive user experiences. • Deploy and manage containerised applications on Kubernetes with comprehensive observability. • Write thorough tests (frontend and backend) and maintain high code quality standards with automated tooling. • Collaborate on architecture decisions and mentor team members on best practices. Qualifications Required Qualifications • Proven experience building and scaling multi-tenant SaaS platforms with strict data isolation. • Strong knowledge of API design, RESTful principles, and OpenAPI specifications. • Proficiency in modern JavaScript frameworks (React, Vue, or Svelte) with TypeScript. • Experience building data-intensive dashboards with complex visualisations and real-time data. • Strong CSS/styling skills and responsive design principles. • Demonstrated experience working with production AI/ML systems at scale. • Practical experience integrating LLM APIs and managing inference at scale. • Understanding of LLM operational challenges: rate limiting, cost optimisation, latency management, fallback strategies. • Familiarity with AI agent frameworks (LangChain, AutoGen, MCP, or similar). • Knowledge of prompt engineering, semantic search, and vector databases. • Hands-on experience with one of the major cloud platforms (GCP, AWS, or Azure). • Strong Kubernetes and Docker skills with production deployment experience at scale. • Experience with workflow orchestration engines (Airflow, Prefect, Temporal, Dagster, or similar). • Proficiency with infrastructure-as-code, GitOps, and CI/CD pipelines. • Understanding of distributed systems, networking, load balancing, and service mesh architectures. Preferred Qualifications • Familiarity with AI safety, red teaming