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We are looking for a Senior Cloud Engineer to join our Infrastructure team in Tel Aviv. In this role, you will be a key contributor to our AWS CDK projects, taking end-to-end ownership of high-impact infrastructure shifts like our migration to EKS. This is a hands-on position where youll balance long-term architectural projects with day-to-day support for our R&D teams, ensuring our cloud environment remains scalable, secure, and developer-friendly.

Responsibilities:
As a Senior Cloud Engineer, you will be the backbone of our infrastructure, ensuring that our cloud environment is scalable, secure, and developer-friendly. You will:

Serve as a core contributor to our central AWS CDK (TypeScript) project, ensuring every cloud resource-from S3 buckets to complex networking rules-is defined as code.

Act as a consultant for R&D and platform teams, helping microservice owners deploy new services and spin up sandbox environments while maintaining security standards.

Take end-to-end ownership of high-impact infrastructure shifts, including playing a key role in the transition from ECS Fargate to EKS.

Manage the lifecycle and maintenance of critical infrastructure components, such as security/observability agents and hosted open-source solutions.

Collaborate with our Boston-based teams on shared global projects to ensure architectural alignment and cross-region infrastructure support.

Balance long-term project work with active participation in internal help channels, troubleshooting real-time issues and resolving conflicts in central tools.

We are looking for an AI Research Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
You'll own technically difficult problems before the solution is known. Starting with a cybersecurity need, you'll study the domain, frame the technical challenge, investigate possible approaches, and build the solution through production. You'll have access to our company's shared agent infrastructure, but the role goes far beyond configuring existing components. Many use cases will require new reasoning methods, agent architectures, evaluation techniques, data strategies, or model behavior. This is a role for someone who enjoys applied research but is motivated by outcomes. The goal is not simply to prove that an idea can work, it is to make it useful and reliable for customers.
What You'll Do:
Design and implement AI solutions for complex cybersecurity workflows.
Develop new approaches for agent reasoning, planning, tool use, context management, decision-making, and recovery from failures.
Determine the right technical approach for each problem, combining models, algorithms, data, and conventional software where appropriate.
Define quality for each use case and create evaluations that measure correctness, task completion, consistency, safety, latency, and cost.
Analyze agent behavior deeply, identify the underlying causes of failures, and improve the relevant model, data, tool, or architecture.
Collaborate with cybersecurity experts, product teams, software engineers, and AI infrastructure engineers throughout development.

We are looking for a DevOps Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
We are looking for a DevOps Engineer to build the backbone of our autonomous security platform. You will manage the infrastructure that powers our Agentic AI workflows, ensuring high performance, scalability, and security for systems that operate independently.
What You'll Do:
Build and scale our cloud infrastructure to support high-throughput AI-driven workloads.
Manage and optimize the production environment for autonomous agent workflows.
Design and maintain robust CI/CD pipelines for fast and reliable deployments.
Monitor system health, scalability, and costs in a complex security environment.

Were looking for a top-notch Detection Software Engineer to join our Threat Research team and further develop the Runtime Sensor. In this role, you will work on a world-class runtime security solution affecting some of the largest cloud workloads, collaborating closely with engineering and research to enable new and better threat detection capabilities.
Check out some of our recent research:
PostgreSQL Cryptomining
SeleniumGreed Cryptomining Exploit Attack Flow & Remediation Steps
PyLoose: First Python-based Fileless Attack on Cloud Workloads
Responsibilities:
Work on a world-class runtime security solution affecting some of the largest cloud workloads.
Work closely with engineering and research to enable new and better threat detection capabilities.
Build and extend our research infrastructure, automated testing infra and release processes.
Conduct research and develop new detection capabilities, from concept to implementation.
Constantly shift things from an art to a science - make the hard things easy, fast and scalable.
Quickly address gaps and changes when needed. Bias towards action.
Analyze, debug and solve problems in test, staging and production environments.
Create and enforce best practices and security policies.
Work with customers in response to requests and questions when needed.

We are looking for a hands-on IT Systems Engineer to own and manage our corporate IT infrastructure. Since our entire fleet is 100% macOS, we need someone with deep, expert-level knowledge of the Apple ecosystem. Additionally, you will bridge the gap between IT and DevOps, helping to automate workflows, manage cloud-based identity tools, and handle basic infrastructure tasks.
What Youll Do:
Mac Management & Security: Own the deployment, configuration, and security of all corporate Mac endpoints using MDM solutions (Jamf Pro / Kandji).
Automation & Scripting: Write scripts (Bash / Python) to automate routine IT tasks, software updates, and onboarding workflows.
DevOps Touchpoints: Manage identity and access (IdP) like Okta/Google Workspace, and collaborate with the R&D team on basic cloud infrastructure, CI/CD, or network security tasks.
IT Infrastructure: Handle SaaS vendor management, network troubleshooting, and security compliance (SOC2).

We are looking for a Software Engineer - Customer Solutions to help customers successfully integrate, configure, and deploy our platform. You will work directly with customers to understand their technical requirements, build integrations, and troubleshoot issues across APIs, data, authentication, and enterprise systems.
This role is ideal for someone who enjoys combining hands-on engineering with customer interaction. We are looking for strong technical fundamentals, curiosity, clear communication, and a practical approach to solving real-world problems.
What Youll Do:
Work directly with customers to understand their technical workflows and integration needs.
Build and configure integrations between our platform and customer systems.
Develop backend services, scripts, APIs, data transformations, and automation workflows.
Investigate technical issues involving APIs, databases, authentication, customer data, and infrastructure.
Participate in customer implementation meetings and help translate business requirements into technical tasks.
Test, deploy, monitor, and support customer-facing solutions.
Document integrations, troubleshooting steps, and implementation decisions.
Work closely with senior engineers and product teams to turn customer-specific needs into reusable capabilities.
Gradually take ownership of increasingly complex customer projects.

We are looking for a mission-driven BizOps Engineer to join our R&D team!
We specialize in advanced AI predictive models, focusing on LTV, churn, and intent to drive business growth.
As the BizOps Engineer, you will serve as both a platform architect and a hands-on builder. You will own the AI-native platform architecture and governance for all non-core product functions, including Sales, Operations, HR, Legal, and Finance, while also building, maintaining, and scaling custom AI solutions yourself to address specific departmental needs.
Reporting directly to the VP of R&D, this role begins as a high-impact Individual Contributor (IC) with a clear mandate to build and lead a dedicated engineering team as the function scales. Your primary focus will be designing and deploying infrastructure and security protocols while simultaneously delivering the bespoke AI tools that empower teams and drive operational efficiency.
You will have the autonomy to choose the most effective path forward for any given challenge, whether that means leveraging existing SaaS platforms, integrating open-source projects, or building custom solutions from scratch, always guided by the specific needs and projected ROI of the departments you support.
Responsibilities:
Architect and maintain the internal AI-native platform, while personally building and scaling custom AI solutions and automated workflows for cross-functional teams.
Establish and enforce security protocols, governance frameworks, and best practices to enable safe and compliant AI solution development across the organization.
Identify and scale platform enablement opportunities that allow departments to automate their own workflows using approved AI capabilities.
Monitor and manage organizational compliance for internal AI applications, ensuring data privacy and ethical standards are met at scale.

As a Staff Engineer, youll play a leading technical role across our Data & AI domains - agent workflows, close management, and data & network. Youll design and build the foundational systems that power these products, working on high-impact, mission-critical services and helping set the technical bar for the team.
What youll do:
Own features end-to-end - Take ideas from early concept through production across agent workflows, close management, and data & network. You wont just write code - youll ship real systems, iterate quickly, and see the impact of your work in production.
Think beyond the task - Take initiative, understand the broader system and business context, and help drive both product and technical decisions. This is not a ticket-driven role.
Leverage AI-accelerated development practices - Use modern AI coding tools to improve development velocity, code quality, and testing efficiency while building robust, secure, and scalable infrastructure.
Backend-focused, full-stack mindset - Your core focus will be backend systems across agent workflows, close management, and data & network, but youre comfortable operating across APIs, data, infrastructure, and DevOps when needed.
Mentor and guide the team - Support and mentor engineers, and guide architectural decisions to raise the technical bar across the team.
Partner across stakeholders - Work closely with Product and Engineering Management to ensure alignment on mission, prioritization, and team focus. Be a focal point for engineering questions, bringing a business mindset and a clear understanding of our goals.
Design for scale - Build backend services that are reliable, maintainable, and architected to scale with the platform.

Were looking for a talented AI-native Software Engineer to join our innovative R&D team!
we help its customers acquire better users and spend less doing it - and our core team owns the engine behind it. We turn raw customer data into ad-network conversions, end-to-end: through large-scale ML and data pipelines, event-driven delivery services on AWS, and the UI that ties it together. There's no narrow lane here - you own problems wherever they live in the stack.
We're an AI-native team: we treat AI and agentic tooling as a first-class part of how we build, and it's how a small team credibly owns this much surface area. We're looking for a high-ownership generalist who works this way (or is hungry to), and who thrives in a correctness-critical domain where a bug means real customer ad-spend going the wrong way.
Responsibilities:
Turn raw customer data into ad-network conversions end to end, building across the whole stack: ML and data pipelines, delivery services, and the customer-facing UI.
Take features from idea to production largely on your own, designing, shipping, monitoring, and iterating, using AI and agentic tooling as a force multiplier, and owning your systems in production where mistakes translate directly into customer spend.
Collaborate closely with the team lead, product, and data scientists to take models and ideas from prototype to reliable, scaled-up production.

We are looking for an Automation Infrastructure Engineer to join our Release Management Squad (RMS) and contribute to the development and day-to-day operation of our automated testing platform. The role focuses on supporting automation infrastructure, CI/CD validation flows, test environments, and visibility into automation results. Working with experienced engineers, R&D, and DevOps, you will help troubleshoot automation issues, improve existing solutions, and expand functional and non-functional validation coverage.
Responsibilities
Develop and maintain automation components for functional and non-functional testing under the guidance of senior team members.
Support the stability of automated validation systems by monitoring executions, investigating failures, and implementing fixes.
Maintain and improve existing automation dashboards, alerts, and quality indicators.
Support CI/CD pipelines and automated quality checks, including troubleshooting validation failures.
Implement test flows for performance, reliability, stability, and upgrade validation based on defined plans.
Set up and maintain automation environments for supported product configurations.
Collaborate with development, QA, and DevOps teams to integrate and execute automation throughout the delivery lifecycle.
Contribute to ongoing improvements in automation tools, infrastructure, documentation, and team practices.

We are looking for Pre-Sale Engineer to join a fast-growing company operating in the defense, drones and autonomous systems space.
The company develops advanced communication and cybersecurity solutions for mission-critical platforms used by global customers and leading system integrators.
The role combines deep technical understanding with hands-on pre-sale activities, working closely with sales teams and customers on RF-based communication solutions and our cybersecurity software.
Responsibilities:
Lead technical aspects of the sales process across Israel, Europe and the US
Work closely with sales teams in customer-facing engagements
Lead technical discussions, presentations, and evaluations with customers and partners
Prepare and respond to RFI/RFPs and develop technical proposals
Translate customer requirements into tailored technical solutions
Analyze and support RF link feasibility based on customer needs
Support the integration and technical aspects of our cybersecurity solutions in customer engagements
Support demos, POCs, and technical evaluations
Collaborate with R&D, Product and Customer Success teams
Provide technical support in early deployment stages when needed.

As an AI Product Manager on the Paradox team, you will own the product lifecycle for core LLM-powered capabilities across candidate and recruiter experiences.
Youll drive product discovery, define requirements, and partner with engineering and data science from design through launch, iteration, and ongoing optimization.
One key part of this role is hands-on AI evaluation. You will regularly review LLM outputs and AI conversation logs, perform data labeling, and dig into traces to identify gaps, edge cases, and failure modes. Youll translate these insights into concrete changes to prompts, data, workflows, and system logic that measurably improve quality, reliability, and user experience.
You will:
Own AI-driven features, including candidate and recruiter-facing experiences.
Define product vision, goals, and roadmaps for your areas, balancing user value, technical feasibility, and business impact.
Lead rigorous evaluation of LLM behavior: review outputs, label data, and partner with data science to refine prompts, metrics, and evaluation strategies.
Collaborate closely with engineering to design scalable, robust solutions and iterate quickly on experiments.
Synthesize input from customers, internal stakeholders, and the market into clear, prioritized product requirements.
Communicate progress, tradeoffs, and learnings across a global, cross-functional set of partners, guiding teams toward high-impact outcomes.
This role is ideal for someone excited to be in the weeds with AI systems-understanding how they behave, why they fail, and what to adjust to make them meaningfully better for real users.

Are you an analytical person who is deeply interested in AI and LLM technology?
Is your superpower accurately categorizing information and identifying patterns?
Do you love to solve interesting challenges and make a direct impact through your work?
Join our Tel Aviv team as an AI Data Analyst and help shape the future of AI. We're looking for analytical minds to contribute to our cutting-edge Large Language Model (LLM) project. In this unique role, you'll be performing LLM data quality tasks, ensuring consistency and quality in our conversations and helping design and support our flagship products.
This is more than a traditional data-labelling role. You will combine hands-on evaluation work with analytical thinking to help shape how our AI experiences evolve.
Sound like your perfect fit? We want to hear from you!
As an AI Data Quality Analyst, you will evaluate LLM-generated conversations and other text-based data, identify trends and regressions, and partner with AI Engineers and Product Managers to improve model performance. In this role, you will:
Review and evaluate LLM-generated conversations and other text-based outputs against task-specific quality criteria and success metrics.
Perform high-quality annotation and data labeling to create reliable datasets for model training, benchmarking, and evaluation.
Monitor real production data to identify quality trends, regressions, and areas for improvement.
Identify qualitative patterns, recurring failure modes, regressions, and opportunities to improve model behavior and user experience.
Analyze evaluation results and clearly communicate insights, risks, and recommendations to cross-functional stakeholders.
Work closely with our AI Engineers and Product Managers to understand the data needs and ensure data quality processes align with goals, ensuring Paradox and our company products remain top in class.