דרושים » הנדסה » Software Engineer, Data Core

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools: Utilize platforms such as Gemini, Claude, and Cursor for tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows: Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards: While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents: Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

As a Senior or Principal Software Engineer in Cortex Cloud, you will contribute to the development and scaling of cloud-native security solutions for enterprise organizations. This role involves working within an established team to evolve a high-traffic product, with a focus on refining architecture, optimizing the technology stack, and maintaining engineering standards.
Your responsibilities include writing reliable code, influencing product direction, and designing distributed systems. You will be expected to make technical decisions that impact the long-term stability and performance of cloud workload protection services.
AI Integration & Engineering Workflow
A core component of our development process is the use of AI. Rather than basic code completion, we integrate AI assistants as functional components of our workflow. Our team utilizes a multi-agent AI system (IDEX/ProDex) that assists across the development lifecycle: from planning and architecture to code analysis and security reviews.
In this role, you will:
Work with AI Tools:Utilize platforms such asGemini, Claude, and Cursorfor tasks beyond code generation, including root-cause analysis, system design reviews, and architectural assessment.
Develop AI-Augmented Workflows:Help refine how AI is integrated into the SDLC, including the orchestration of agents and the development of internal tools that extend AI capabilities across our codebase.
Maintain Quality Standards:While AI assists in increasing velocity, you are responsible for the technical output. This includes critical review of all generated code and ensuring that AI-assisted work aligns with our architectural requirements and security benchmarks.
Interact with Specialized Agents:Coordinate with AI agents (Product, Architecture, Security) that operate on shared context to assist in managing complex engineering tasks.
We are looking for engineers who are interested in leveraging AI as a technical tool to manage complexity and who want to contribute to the practical application of human-AI collaboration in a cloud environment.

Your Role:
Lead the design and development of complex, high-performance, backend services within the One ecosystem, ensuring modularity and long- term maintainability.
Own the end-to-end performance of critical platform components, optimizing for massive data ingestion and low-latency processing across global environments.
Drive architectural discussions and provide high-level input on system design, steering the team toward scalable, cloud-native best practices.
Actively mentor and contribute to code reviews and technical discussions, sharing expertise and fostering a collaborative environment for continuous improvement.
Collaborate closely with Product, SRE, QA and Security teams to implement technical solutions aligned with business objectives.
Take a production-first approach to reliability; lead root cause analysis for complex distributed system issues and implement preventative measures to guarantee system reliability.

Your Role:
Lead the design and development of complex, high-performance, backend services within the One ecosystem, ensuring modularity and long- term maintainability.
Own the end-to-end performance of critical platform components, optimizing for massive data ingestion and low-latency processing across global environments.
Drive architectural discussions and provide high-level input on system design, steering the team toward scalable, cloud-native best practices.
Actively mentor and contribute to code reviews and technical discussions, sharing expertise and fostering a collaborative environment for continuous improvement.
Collaborate closely with Product, SRE, QA and Security teams to implement technical solutions aligned with business objectives.
Take a production-first approach to reliability; lead root cause analysis for complex distributed system issues and implement preventative measures to guarantee system reliability.

we are seeking a Hands-on Architect to design, build, and evolve the core of next-generation AI cybersecurity platform.This is not an ivory-tower role; it is for a builder at heart. You will write code, build functional prototypes, and own critical services from inception to production. This role demands a unique blend of deep, code-level execution with a broad, system-wide architectural vision that spans our entire data, cloud, and AI stack.
Responsibilities:
Rapidly code and build functional proofs of concept (PoCs) and prototypes to explore and validate new architectures, data platforms, data processing frameworks, and GenAI capabilities.
Validate technical feasibility, scalability, and business impact through working software, not just diagrams or documents.
Partner closely with engineering, product and data science teams to translate emerging technologies into production-ready, scalable systems.
Lead architecture design reviews, proactively identify scalability and performance bottlenecks, and embed security principles into the design process from day one.
Serve as a technical leader and mentor, elevating the team's skills through pair programming, in-depth code reviews, and deep-dive sessions on system design and software craftsmanship.

Your Role:
Lead the design and development of complex, high-performance, backend services within the One ecosystem, ensuring modularity and long-term maintainability.
Own the end-to-end performance of critical platform components, optimizing for massive data ingestion and low-latency processing across global environments.
Drive architectural discussions and provide high-level input on system design, steering the team toward scalable, cloud-native best practices.
Actively mentor and contribute to code reviews and technical discussions, sharing expertise and fostering a collaborative environment for continuous improvement.
Collaborate closely with Product, SRE, QA and Security teams to implement technical solutions aligned with business objectives.
Take a production-first approach to reliability; lead root cause analysis for complex distributed system issues and implement preventative measures to guarantee system reliability.

We are looking for a driven, technically curious Staff Backend Developer to join a cutting-edge team focused on Agentless Scanning within Cortex Cloud, our company's next-generation cloud security platform. Based in our Tel Aviv (TLV) office, you will be at the forefront of cloud security innovation. Our team's mission is to help Cortex Cloud customers discover, understand, and fix security vulnerabilities in their workloads across all major cloud providers. This role is ideal for a proactive engineer with a strong "can-do" attitude, a passion for solving complex technical problems, and a desire to grow rapidly alongside experienced mentors. If you love digging into backend systems and want to see your code directly impact global enterprise customers, we want to hear from you!
Your Impact
Hands-on Backend Development: Contribute to the design, development, testing, and deployment of features and core components within the Agentless domain.
Feature Ownership: Collaborate closely with senior team members and partners across Cortex Cloud to deliver high-quality features from inception to production.
Customer-Centric Problem Solving: Help build robust solutions that address the day-to-day security challenges faced by our customers.
Continuous Learning & Collaboration: Actively participate in team-wide engineering practices, including code reviews, technical discussions, and agile processes, to continuously elevate your skills.

We are looking for a Senior DevOps Engineer to join our R&D team in developing the next rising product in the health tech landscape. If you are looking for a challenging, influential position and are passionate about making an impact, this might be the role for you.

As a Senior DevOps Engineer , youll play a key role in the design, development, testing, deployment, and monitoring of our infrastructure and products. In this position, you'll make significant contributions to our observability stack, helping build and maintain robust systems for logs, metrics, traces, and alerting.

Our ideal candidate is passionate about DevOps and observability, has strong communication skills, and thrives on constant improvement for both technology and processes. If you enjoy working on multiple projects in parallel and are a proactive team player, youll fit right in.

This is a unique opportunity to join the core team of a fast-growing startup, where your contributions will have a direct impact on our product and success.

Responsibilities

Support and collaborate with cross-functional engineering teams using cutting-edge technologies.
Contribute to the design, implementation, and maintenance of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, Loki)
Secure, scale, and manage our cloud environments (AWS and GCP)
Design and implement automation solutions for both development and production
Manage and improve our CI/CD pipelines for fast and safe delivery
Lead best practices in infrastructure, observability, configuration management, and system hardening
Continuously assess and improve existing infrastructure in line with industry standards

The Data Engineering team is a cross-functional team responsible for data integration, monitoring, and quality. This includes automating data flows, alerting, fetching, and checking across various stages of data transformation and projection.
Key Responsibilities
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Develop data architecture for data ingestion, validation, and processing.
Identify, design, and implement process improvements, such as automating manual tasks, optimizing data delivery, and redesigning infrastructure for enhanced scalability.
Create and maintain optimal data pipeline architecture using microservices.
Work with other members of the data team, including data architects, data analysts, and data scientists.
Key Takeaways
Use the tools and languages that are best suited to the job - Complete flexibility to problem-solving with novelty and creativity encouraged.
Be around very bright and lovely people.
Your intellectual curiosity and hard work contributions will be welcome to our culture of knowledge sharing, transparency, and shared fun and achievement.
Provide education and documentation to empower team members to make the most of technical resources.
Contribute to our software engineering culture of writing correct, maintainable, elegant, and testable code.
Utilize AWS services and tools such as S3, EventBridge, Athena, and DynamoDB to build a robust and scalable data architecture for data ingestion, processing, and storage.
Collaborate on data infrastructure that supports LLM-driven workflows - leveraging tools like Cursor to accelerate code development, enhance reproducibility, and streamline iteration on intelligent systems.

We are looking for a Senior Software Engineer to join the AIOps platform team and help build the core distributed systems that ingest massive telemetry streams from GPU clusters and operationalize predictive AI models at scale. You will work at the intersection of high-performance data engineering and production ML, turning research algorithms into reliable, mission-critical software.

What you'll be doing:

Architect and build an agentic AIOps system that autonomously monitors GPU fleet health, aggregates and correlates massive telemetry streams, surfaces intelligent alerts, and orchestrates multi-step diagnostic workflows and corrective actions - powering real-time dashboards, automated root-cause analysis, and proactive incident response.

Research, evaluate, and prototype data storage strategies and data representations across diverse database technologies and modalities, ensuring AI models are trained on high-quality, well-structured data that improves predictive accuracy and generalization.

High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.

Instrument services with deep observability (metrics, logs, traces) to support rapid debugging and continuous performance improvement.

Build and own the model-serving infrastructure that operationalizes predictive algorithms at scale - packaging, versioning, deploying, and monitoring AI models in both SaaS and on-premises environments.

Contribute to the platform's core libraries and abstractions that accelerate development across the broader AIOps engineering team.