Required Senior ML Engineer - Applied AI Engineering Group
The Dream Job
It starts with you - an engineer driven to build the ML platform that turns research into reliable, production-grade intelligence. You care about reproducibility, low-friction experimentation, and infrastructure that earns the trust of the scientists and researchers who depend on it daily. You'll architect and ship our ML platform - training pipelines, model serving, feature stores, experiment tracking, and compute orchestration - turning models into production capabilities across cloud and on-prem, including air-gapped deployments. A significant part of the platform supports large language models, with unique challenges across training, evaluation, and inference in mission-critical environments.
If you want to make a meaningful impact, join our mission and build the ML platform that drives Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.

we are looking for a Senior Data Engineer I.
As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.
Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.
Key Job Responsibilities and Duties:
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Dealing with massive textual sources to train GenAI foundation models.
Solving issues with data and data pipelines, prioritizing based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that improve Data Quality company-wide, specifically for ML scientists.
Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
Acting as an intermediary for problems, with both technical and non-technical audiences.
Promote and drive impactful and innovative engineering solutions
Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.
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We are looking for a highly skilled and motivated Senior II Software Engineer to join the Operational Experience engineering team. The team is part of the Customer Experience group, which is responsible for the platform, tools, and customer-facing experiences that power how our customers interact with our ecosystem. This is a high-impact, hands-on role, in which youll be working closely with product managers, designers, customer-facing teams, and engineering partners across the company.
You will operate at the intersection of backend engineering, data-intensive systems, platform development, and customer experience. The ideal candidate brings strong expertise in Node.js and TypeScript, along with deep experience working with large-scale data stores, event-driven pipelines, data models, and high-throughput infrastructure. You will work closely with cross-functional partners to design and implement robust backend services, data-access patterns, and operational workflows that power the portal and internal tools. As we invest heavily in Agentic AI, you will also play a central role in shaping and implementing AI-driven capabilities across the platform. While the role is primarily backend, you will occasionally contribute across the full stack when it supports end-to-end delivery.
If you enjoy owning complex problems end to end, improving systems at scale, and building experiences that bring real value to customers, we would love to meet you.
What you'll be doing:
Drive technical direction and architecture within the OX team and across the broader CX organization. You will proactively identify opportunities to improve performance, resilience, cost, scalability, and developer experience, primarily in backend systems but with influence across the stack.
Lead the development of AI-driven and Agentic AI capabilities. Define how LLMs integrate into our platform, build AI-powered workflows, and establish strong engineering patterns for safe and reliable adoption.
Own and evolve the data foundations behind the portal. Optimize pipelines, improve data quality and freshness, and design resilient data-access patterns across Snowflake, Elasticsearch, Kafka, Redis, MySQL, and related systems.
Work closely with product, design, customer-facing teams, and partner engineering groups. Turn ambiguous problems into clear execution plans and ensure alignment with customer and business goals.
Shape shared standards and platform best practices. Guide other teams on backend services, data integration patterns, portal development approaches, and AI-enabled workflows.
Mentor and elevate engineers across the CX group. Promote engineering excellence, share knowledge openly, and help teams adopt effective modern development practices.
Own delivery of high-impact initiatives. Contribute hands-on when needed, remove blockers, maintain execution momentum, and drive projects from concept to production.

We are looking for a Senior Software Engineer to join our CI Infrastructure team within the Platform Engineering organization.
The team designs, builds, and operates the internal engineering platform that powers our companys build, test, and security validation workflows. This includes large-scale orchestration of complex test environments, hybrid cloud/on-prem execution infrastructure, DevSecOps integrations (SCA, SAST, policy enforcement), and advanced optimization mechanisms.
Our mission is to provide a scalable, reliable, and intelligent CI platform that enables hundreds of engineers to build and validate a complex distributed networking product efficiently and safely.
This is a hands-on engineering role focused on scalability, observability, reliability, and intelligent automation, with direct impact on engineering velocity and release confidence.
What Youll Do
Design and evolve scalable CI infrastructure for build and large-scale test execution
Develop automation and orchestration systems across hybrid environments (AWS and on-prem)
Integrate and optimize security validation flows (SCA, SAST, quality gates) within CI
Improve reliability, performance, and observability across high-volume CI workloads
Develop AI-assisted tooling and agents to optimize test selection, failure analysis, and resource utilization
Analyze CI data to identify bottlenecks, flakiness patterns, and optimization opportunities
Collaborate with R&D, Automation, and Security teams to continuously improve CI architecture and best practices
Take ownership of critical platform components used daily by large engineering teams.

We are looking for a highly motivated AI Full stack Engineer with GenAI background in production to join our team and help us shape the future of the Agentic engineering platform (AEP).
What youll do:
At our company, were a platform by developers, for developers. Your role will encompass end-to-end design, implementation, and daily feature delivery across both backend and frontend systems.
You will:
Implement high scale AI-powered features deeply integrated into our platform
Design and build production-grade backend systems serving a wide and growing user base
Build agent-based workflows using frameworks such as AI SDK
Integrate LLMs into real production systems with attention to reliability, latency, observability, and cost
Work across frontend (React + TypeScript) and backend (NodeJS, Python, Go) to deliver complete AI-driven user experiences
Own features end-to-end: design, implementation, testing, deployment, and monitoring
Help define standards and best practices around AI reliability and evaluation
Contribute to technical planning, mentor teammates, and help recruit top talent
Develop retrieval-augmented generation (RAG) pipelines over structured and unstructured data
Our stack includes React + TypeScript on the frontend, and NodeJS + TypeScript, Python, and Golang on the backend, and Vercels AI-SDK + AWS Bedrock + Azure OpenAI for GenAI. We use Kafka + Kafka Connect, Redis, PostgreSQL, MongoDB and other modern infrastructure components.

Were looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
Key Responsibilities:
Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

Required Senior Software Engineer - CWPP Team
About the role:
As a Senior Software Engineer on the CWPP (Cloud Workload Protection Platform) team, youll be part of a core group responsible for protecting our customers cloud workloads at scale. Our team scans and analyzes a wide variety of cloud assets - from virtual machines and container images to object storage buckets and databases, to uncover vulnerabilities, secrets, misconfigurations, and other security risks.
This role offers a unique opportunity to build the infrastructure that powers our deep forensics engine. Youll help reconstruct customer file systems across multiple operating systems, extract OS-level and application-level metadata, and enable our security researchers to detect threats and vulnerabilities quickly and reliably. Your work will directly impact the safety and security of thousands of cloud environments worldwide.
Were looking for engineers who are passionate about operating system internals, large-scale distributed systems, and cloud security, and who want to make a meaningful impact by building robust, high-performance security platforms. This is also a great opportunity to take ownership, lead initiatives, and grow through collaboration, mentorship, and technical leadership.
Our Stack: Python, Linux & Windows internals, Container Runtimes, Postgres, Redis, Kafka, AWS, GCP, Azure
On a typical day youll:
Design, implement, and maintain scalable backend services for scanning and analyzing cloud workloads (VMs, containers, buckets, databases, etc..)
Build infrastructure for reconstructing file systems across different operating systems (Linux and Windows) to enable deep analysis
Integrate security detection engines for vulnerabilities, secrets, compliance, and malware
Collaborate with security researchers and product managers to translate complex requirements into impactful product features
Write clean, efficient, and testable code, ensuring high performance and reliability
Participate in design and code reviews to uphold technical excellence and team standards
Lead features end-to-end - from design and planning to deployment and monitoring
Improve system observability, performance, and resilience in production environments
Stay current with developments in the cloud security landscape, vulnerability management, and OS internals.

We are looking for a Senior Software Engineer to join our Decision Engineering team. The group is responsible for the real-time, low-latency infrastructure that powers our fraud decisions and external APIs.
Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.
In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.
This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of our decisioning platform.
What you'll be doing:
Design, build, and scale backend systems that power our real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across our decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.