We are looking for a Senior Software Architect to lead the architecture and technical execution of Aqua’s AI products and shared AI capabilities.
This is a strategic and hands-on role for an architect who combines strong backend and distributed-systems expertise with practical experience in data platforms, cloud architecture, web technologies, and AI systems.
You will own the technical architecture from early concepts and proofs of concept through production delivery and operation. You will work closely with engineers, product managers, security researchers, and architects to turn emerging AI capabilities into secure, scalable, reliable, and maintainable products across SaaS and on-premises deployments.
The successful candidate will provide hands-on technical leadership, help engineers resolve complex design and implementation decisions, and ensure that the architecture supports product quality, operational simplicity, and long-term evolution.
What You Will Own
Define and drive the architecture of Aqua’s AI-powered products and shared AI capabilities across SaaS and on-premises deployments.
Design scalable backend services, APIs, data pipelines, data models, and storage solutions for AI and security workloads.
Lead architectural decisions across data ingestion, processing, retrieval, model integration, AI orchestration, and product integration.
Work closely with engineers throughout design and implementation, helping resolve complex technical decisions, trade-offs, and delivery challenges.
Provide hands-on technical leadership from early concepts and proofs of concept through production delivery and operation.
Design systems with clear controls for scalability, backpressure, bounded resource usage, resilience, data integrity, recovery, and observability.
Ensure solutions meet enterprise requirements for security, isolation, permissions, auditability, sensitive-data handling, and on-premises operation.
Define patterns for integrating AI models, retrieval systems, tools, workflows, and deterministic product capabilities.
Design AI-enabled workflows with quality, latency, cost, failure handling, model limitations, and operational complexity in mind.
Support the architecture and development of web-based AI experiences and their integration with backend services and Aqua product workflows.
Evaluate technologies and conduct proofs of concept to validate feasibility, performance, scalability, security, and operational fit.
Define and document architecture standards, technical guidelines, and reusable patterns for the AI team.
Review system designs and critical implementations, and mentor engineers on architecture, backend development, data systems, and production readiness.
Collaborate with Product and Engineering to balance customer value, delivery speed, technical risk, and long-term maintainability.
Partner with other architecture and platform teams to reuse existing capabilities and maintain alignment across Aqua products.
About the Team
Requirements
8+ years of experience designing and building backend systems, including large-scale or distributed production systems.
Strong hands-on backend development experience, preferably with Python and Go.
Proven experience designing scalable APIs, services, data pipelines, and data-processing systems.
Strong knowledge of data modeling, relational databases, indexing, caching, and storage-system trade-offs.
Experience designing cloud architectures, preferably on AWS.
Experience designing products for both SaaS and on-premises deployments.
Strong understanding of Kubernetes, containers, distributed systems, networking, and modern deployment practices.
Experience designing systems for reliability, scalability, security, observability, recovery, and operational simplicity.
Experience with modern web development, including React, TypeScript or JavaScript, and npm.
Experience leading technical decisions from early concepts and proofs of concept through production delivery.
Experience driving architectural alignment across engineering, product, research, and architecture teams.
Demonstrated ability to work closely with engineers and provide practical guidance during implementation.
Excellent communication, technical documentation, and system-design skills.
Hands-on, pragmatic, and collaborative approach, with the ability to balance short-term delivery and long-term architecture.
Bachelor’s degree in Computer Science or equivalent practical experience.
Nice to Have
Experience building AI, machine learning, analytics, or other data-intensive products.
Understanding of LLM-based architectures, including model integration, retrieval, tool execution, orchestration, and evaluation.
Experience designing AI-enabled workflows with cost, isolation, resilience, security, and quality controls.
Experience with vector search or similar technologies.
Experience building high-volume or near-real-time data pipelines.
Background in cloud security, cybersecurity, DevSecOps, or cloud-native products.
Experience supporting AI capabilities in restricted, disconnected, or resource-constrained on-premises environments.
Experience taking an AI or machine learning capability from early concept through production operation.
