This is a strategic, high-impact role focused on designing scalable, resilient, and data-driven cloud architectures that power large-scale enterprise security workloads. You will define architectural standards, influence long-term platform evolution, and ensure our systems are built for performance, reliability, and continuous innovation.
You will collaborate closely with Engineering, Product, and Security Research leadership to drive architectural excellence across the organization.
What You Will Own
Lead the architectural strategy and evolution of our SaaS platform.
Design scalable system structures with a strong focus on data modeling, storage strategies, and high-performance workloads.
Define architecture standards, best practices, and governance guidelines across engineering teams.
Architect high-volume, real-time, and analytical data pipelines.
Design and optimize schemas, indexing strategies, caching layers, and storage patterns.
Evaluate and introduce technologies that improve scalability, performance, and observability.
Provide hands-on technical leadership from concept through production deployment.
Conduct PoCs and architectural evaluations to guide long-term strategic decisions.
Mentor engineering teams on distributed systems design, microservices patterns, and data architecture.
Align architectural direction with business goals and product strategy.
Design AI-enabled and agentic workflows with strong considerations for cost efficiency, isolation, resilience, and runtime safety.
8+ years of experience designing and building large-scale distributed systems.
Proven expertise in complex data architecture design (schema design, indexing, caching, governance).
Strong backend development experience (Go, Java, or similar).
Deep experience with modern data storage technologies (PostgreSQL, MongoDB, Elasticsearch, Kafka, ClickHouse, or similar).
Strong understanding of microservices, event-driven systems, and SaaS architecture patterns.
Hands-on experience in cloud-native environments (Docker, Kubernetes, AWS/GCP/Azure).
Experience leading architectural alignment across multiple engineering teams.
Excellent communication, documentation, and cross-functional leadership skills.
Strong understanding of modern AI-driven architectures, including LLM orchestration, tool execution frameworks, and runtime safety considerations.
Ability to design AI-enabled systems with performance, isolation, and resilience at scale.
B.Sc. in Computer Science or equivalent experience (advanced degree or elite technical unit background – advantage).
