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Senior Software Architect
לא צויןמשרה מלאהAI EngineeringCybersecurity
Lead architecture for AI-powered products, integrating AI into scalable, secure systems. Drive decisions across backend, data, and AI orchestration. Ensure enterprise-grade security, observability, and operational simplicity.
תחומי אחריות
- Define and drive architecture for AI-powered products across SaaS and on-premises deployments.
- Design scalable backend services, APIs, data pipelines, and models for AI and security workloads.
- Lead architectural decisions on data ingestion, processing, model integration, and AI orchestration.
- Collaborate with engineers to resolve technical decisions and provide hands-on leadership.
- Ensure systems meet enterprise security, isolation, auditability, and recovery requirements.
- Define patterns for AI model integration, retrieval systems, and deterministic product capabilities.
- Design AI-enabled workflows considering quality, latency, cost, and failure handling.
- Evaluate technologies and conduct proofs of concept for feasibility and performance.
- Document architecture standards and reusable patterns, mentoring engineers on system design.
- Partner with product and architecture teams to balance delivery speed and long-term maintainability.
דרישות
- 8+ years of experience designing and building backend and distributed systems.
- Strong hands-on backend development with Python or Go.
- Proven ability to design scalable APIs, services, and data pipelines.
- Deep knowledge of data modeling, relational databases, indexing, and caching.
- Experience with cloud architecture, preferably on AWS.
- Experience designing products for both SaaS and on-premises deployments.
- Proficiency in Kubernetes, containers, and modern deployment practices.
- Experience building reliable, scalable, and observable systems.
- Familiarity with modern web development using React and TypeScript/JavaScript.
- Excellent communication, documentation, and system design skills.
יתרון
- Experience building AI, ML, or data-intensive products.
- Understanding of LLM architectures, including model integration and orchestration.
- Experience designing AI workflows with cost, isolation, and quality controls.
- Familiarity with vector search or similar technologies.
- Background in cloud security, DevSecOps, or cloud-native products.
- Experience with high-volume or near-real-time data pipelines.
- Track record of taking AI capabilities from concept to production.