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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.

We are looking for a system engineer to join our talented system engineering department.
As a system engineer you will be leading complex, multidisciplinary projects as a the technical owner, processing the customer needs and values into system specifications and requirements, overview the development and chair the acceptance processes.
Responsibilities
Customer Liaison.
Analysis of customer needs and requirements.
Identification of internal Projects Specifications and requirements.
Ability to lead and manage sub-contractors, including contractual engagements and procurement supervision.
Ability to lead a team of engineers, including the management of work plans and delivery schedules.
Ability to create effective and deployable solutions to complex engineering challenges.
Preparing, Leading and participating in Design Reviews and contractual engagements activities.
Leading acceptance and delivery processes with multiple entities, domestically and abroad.

Required Tier 3 Service Engineer
About The Position
Act as the highest level of technical escalation for Tier 1 and Tier 2 service teams, leading the resolution of complex technical issues.
Provide advanced remote technical support to global customers, partners, and field teams, including participation in the on-call rotation for after-hours support.
Lead technical service activities for local customers, including troubleshooting, coordination, issue ownership, and follow-up through resolution.
Collaborate closely with R&D, Quality Assurance, Product, and Operations teams to investigate recurring issues, improve system reliability, and drive effective corrective actions.
Develop, improve, and maintain service documentation, troubleshooting procedures, knowledge articles, and training materials.
Deliver technical training and knowledge transfer sessions to global service teams, distributors, and partners.
Support system validation, software upgrades, service readiness activities, and new product introductions from a service perspective.
Analyze service data, trends, and recurring failure patterns using Salesforce, Excel, BI tools, and other available reporting systems.
Ensure all service activities are performed in compliance with applicable Quality, Regulatory, and Safety standards.

Were at a super exciting inflection point. Our product is scaling, our customers are pushing the boundaries of whats possible, and were re-architecting our platform to keep up with that pace.
Were looking for a Full Stack Engineer who wants to build, not just maintain. Someone who gets excited about laying down core infrastructure, shaping technical vision, and shipping real product fast. This is a hands-on role with tons of room to grow and influence the direction of the company.
What Youll Do
Own big pieces of the product: Youll lead core projects that shape how teams experience our company, making complex workflows feel dead simple.
Ship fast and thoughtfully: We care about great engineering and moving quickly. Youll set the tone for both.
Build the foundation: From infrastructure to frontend components, youll help create the building blocks that unlock entirely new use cases for our customers.
Make us scale like magic: As usage explodes, youll make sure our product stays fast, stable, and elegant behind the scenes.
Collaborate deeply: Youll work side-by-side with design, product, and go-to-market teams to bring ambitious ideas to life, and help shape the technical culture as we grow.

As a Senior Site Reliability Engineer at our company 911, you'll own the infrastructure that keeps our platform reliable, scalable, and secure - work that directly supports mission-critical 911 systems used by public safety agencies. You'll drive infrastructure-as-code practices across AWS, lead observability efforts through Datadog, and bring modern AI-assisted engineering approaches into how the team builds and operates.
What You'll Do
Own and evolve AWS infrastructure using Infrastructure-as-Code (Terraform / Terragrunt)
Architect and scale AWS environments
Deploy, scale, and manage containerized workloads using Kubernetes and Docker; contribute to HA/DR architecture and platform strategy
Lead deployment and release processes using Argo (reference JD also names Bitbucket, Jenkins as part of the CI/CD toolset).
Define and enforce SLOs, SLIs, and error budgets; drive toil reduction across the platform
Drive full utilization of Datadog for monitoring, dashboards, and alerting across the platform (reference JD also names Prometheus, Grafana as potential observability tooling)
Build self-service internal developer platforms that empower teams to ship faster.
Take end-to-end ownership of infrastructure projects - define success criteria, execute, and measure outcomes.
Partner cross-functionally with engineering teams (e.g., network engineering, Dev owners) on long-term technical planning.
Bring AI-assisted engineering practices (e.g., Claude, MCP integrations) into daily workflows to improve team efficiency
Document work and provide cross-training to peers.
Resolve JIRA tickets across Cloud, CI/CD, deployments, and monitoring.

As a quantum researcher, your main role will be to develop algorithmic and error-reduction tools to help our partners and customers achieve quantum advantage for their applications. You will develop our companys error reduction methods, including mitigation and correction, and apply them to different use cases by optimizing existing methods, developing new algorithms, and adapting these tools to the realities of running on quantum hardware. This includes taking into account application requirements, noise characteristics, device constraints, and performance on real quantum devices.
Responsibilities
Developing new error reduction methods, including mitigation and correction, for quantum algorithms.
Optimizing error reduction methods for different algorithms, applications, and hardware settings.
Developing new quantum algorithms to enhance performance on real quantum hardware with error mitigation.
Conducting research on applications of quantum computing with our companys partners, including implementing and running proof-of-concept demonstrations of these applications on real quantum hardware. 

Required Staff GPU Verification Engineer
Join our GPU Hardware Verification team in Raanana, Israel, and help shape the future of the world's most widely deployed GPU architecture - Mali. As a Staff Hardware Verification Engineer, you will play a key technical role in verifying advanced GPU components and subsystems, working alongside architects, designers and verification engineers to deliver high-quality, industry-leading graphics technology. You'll contribute to complex verification environments, solve challenging technical problems and help drive continuous improvements to our verification methodologies and flows.
Responsibilities:
Develop and execute verification plans for advanced GPU components and subsystems.
Develop and maintain AI tools, agents, and skills to support our engineering teams and workflows.
Build, maintain and enhance robust verification environments using SystemVerilog and UVM.
Apply coverage-driven, constrained-random and, where appropriate, formal verification techniques to achieve comprehensive functional coverage.
Debug complex functional issues and work closely with Design and Architecture teams to identify and resolve root causes.
Contribute to block-level and system-level verification, including environment integration and regression analysis.
Improve verification methodologies, automation, scripting and continuous integration flows to increase quality and efficiency.
Participate in verification reviews and support verification sign-off activities.
Share technical knowledge and collaborate with colleagues across the wider GPU engineering organisation.