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We are seeking a talented and experienced Software Engineer to design, build, and optimize high-performance distributed systems, core data engines, and backend infrastructure. This role requires deep system-level architecture understanding, the ability to handle large-scale clusters processing petabytes of data, and mastery of modern C/C++ and Linux environment internals.
Key Responsibilities
Design & Develop Core Components: Build, maintain, and optimize highly scalable, resilient distributed services, storage engines, or data-processing pipelines written in C/C++.
System Architecture & Resilience: Drive architectural discussions and implementations around high availability, data consistency, replication mechanisms, fault tolerance, and multi-node concurrency.
Performance Optimization: Optimize hot execution paths, low-level data structures, memory management, and I/O subsystems to guarantee high throughput and minimal latency.
Complex Debugging & Troubleshooting: Investigate and resolve intricate production issues spanning the application layer, distributed networking protocols, file systems, and operating system kernels.
End-to-End Ownership: Take full technical ownership of critical features-from ambiguous requirements and system design through implementation, rollout, and observability in production environments.
Teams
Storage Platform: Focuses on building a next-generation distributed storage platform handling petabytes of data across large clusters specifically designed to power AI, enterprise, and analytics workloads. Handling everything that touches the hardware and operating system aspects in a software defined storage system
Data Path: Focuses on engineering a highly distributed, latency-critical Hot I/O Data Path and Element Store engine. This role is responsible for the ingestion, state-of-the-art compression, encoding, and retrieval of multi-protocol data (files and objects) under massive concurrency and ultra-low latency requirements.
Database: Focuses deeply on core relational database internals, specifically designing low-level storage engines, B-Tree/LSM-Tree data structures, MVCC concurrency control, and query execution planners.
Kernel: Focuses on the lowest software layers, emphasizing Linux Kernel development and block-level storage/file system engineering.
Protocols: Focuses strictly on engineering high-concurrency data/metadata paths that replicate external AWS S3 object-storage behavior and correctness under heavy retry and failover pressure.
Cloud: Focuses on cloud-native storage deployment, adapting and scaling complex high-availability storage infrastructure across major hyper-scaler cloud environments (AWS, Azure, GCP).
Compute Kafka: Focuses on distributed event-streaming and messaging platforms, specifically building a high-scale, exactly-once broker compatible with the Apache Kafka wire protocol.

LiveU is the global leader in live streaming and remote production, delivering high-quality, low-latency live broadcast solutions worldwide. We generate and process massive volumes of real-time device telemetry, operational data, and business metrics. We are looking for an experienced, hands-on Director of Data & AI join our Information Systems Department . In this role, you will define and drive our enterprise Data, Analytics, and AI roadmap. In this role, you will bridge strategic vision with technical execution- building a scalable cloud data platform, operationalizing production-grade AI, and driving company-wide AI adoption to create measurable business impact. Reporting to VP MIS Location : Kfar Saba (hybrid) Key Responsibilities : AI Enablement & Adoption: Lead company-wide AI literacy, change management, and adoption of GenAI tools (Copilot, ChatGPT Enterprise, custom agents) across R&D, Sales, Support, and Finance. Modern Data Platform: Architect and scale LiveU’s cloud data warehouse, unifying real-time device telemetry with enterprise systems and LivuU product (Salesforce, Priority ERP, AWS, and more). Applied AI & MLOps: Drive AI/ML initiatives from POC to production deployment (predictive models, RAG architectures, and AI agent workflows). Governance, Security & FinOps: Enforce data quality, security (GDPR, SOC 2), and AI guardrails while optimizing cloud compute and licensing costs. BI & Self-Service Analytics: Deliver executive-level dashboards and self-service BI capabilities for faster, data-driven decision-making. Leadership: Lead and mentor a team of data & AI engineers and analysts, fostering a culture of technical excellence and ownership.

we are looking for a Senior Infrastructure Developer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What Youll Be Doing
Design, build and set up development tools and infrastructure for use by the various teams in the R&D organization.
Among the different tools:
test infrastructure used by the QA
Maintain and develop API and interfaces facing the company storage product + different cloud providers.
full stack bug investigation portal
VM orchestration
Collaborate with other teams to improve the productivity of the entire R&D organization.
Dealing with diverse technologies and domains - Docker, Git, Python, Linux, Python, Storage.

Shape the Future of AI Infrastructure with our company
This is a rare opportunity to join one of the fastest-growing infrastructure companies in tech history, right at the epicenter of the AI revolution.
Recognized by Forbes as "the future of the market," our company is building the foundational enterprise software powering the AI era. We engineer platforms that capture, catalog, refine, and protect massive datasets across data centers, edge, and cloud, making real-time analytics, AI training, and inference simpler and faster than ever before.
Our explosive growth is fueled by relentless engineering innovation, a customer-first mindset, and a team of fearless company ronauts who thrive on solving computing's hardest problems. Join us at this pivotal moment in technology history and make a lasting impact on how the world processes data.
We are looking for a hands-on, forward-thinking Security Engineer to join our growing security team. In this role, you will lead offensive security initiatives, build internal automation using modern workflows and AI agents, and manage cloud and infrastructure risks. You will conduct penetration tests across our architecture, analyze deep protocol flaws, write custom tooling, and take security findings from discovery all the way to resolution.
Core Responsibilities:
Penetration Testing & AI Automation: Conduct comprehensive penetration tests across all components of our architecture-ranging from Web APIs down to S3 protocols-and design systems to automate routine pentesting using AI tools.
Protocol & Flaw Analysis: Leverage a deep understanding of network and application protocols to identify architectural and implementation flaws, using AI prompts and modern tooling to uncover edge-case security risks.
Tooling & Process Automation: Write custom internal security tools and leverage AI agents to automate repetitive tasks, incident responses, and continuous security workflows.
Secondary Responsibilities:
Cloud Security Monitoring: Monitor and manage cloud security posture using CNAPP (Cloud-Native Application Protection Platform) tools, maintaining oversight of our cloud infrastructure and containerized environments.
Vulnerability Management & Remediation: Run and maintain regular SAST and DAST scans across operating systems, Docker containers, and source code. Own security findings from discovery through code remediation and validation.
Jira & Delivery Tracking: Manage, prioritize, and promote security Jira tickets through the full lifecycle-from initial triage and assignment through to final delivery and verification.