לוח משרות דרושים הייטק תוכנה בתל אביב יפו

we are looking for a Senior Data Scientist - AI Research Group.
:Responsibilities
Conduct hands-on research and development of state-of-the-art models, algorithms, and systems.
Lead research projects end-to-end from problem formulation, ideation, and experimental design to prototyping and transition into production.
Explore new methodologies and develop creative approaches to solve complex challenges.
Identify ambitious research directions and invent novel approaches to solve complex, high-impact problems.
Shape the research roadmap and influence long-term technical strategy across the organization.

It starts with you - an engineer driven to operate database systems at the highest level of reliability and performance. You care about query latency, uptime, data durability, and getting paged as little as possible. Youll operate, tune, and scale the database engines that serve the platform - from PostgreSQL to Elasticsearch, Redis to vector databases, across cloud and on-prem environments.
If you want to run the databases that power mission-critical AI at national scale, join Dreams mission - this role is for you.
The Dream-Maker Responsibilities
Operate and maintain database systems - PostgreSQL, Elasticsearch, Redis, MongoDB, vector databases, and others across cloud and on-prem.
Own database reliability - high availability configurations, replication, failover automation, and SLA adherence.
Drive performance tuning - query optimization, index design, configuration tuning, and resource profiling to meet latency and throughput targets.
Execute operational procedures - backup/recovery, disaster recovery testing, upgrades, migrations, and capacity scaling.
Lead incident response for database issues - troubleshooting production problems, root cause analysis, and implementing preventive measures.
Build monitoring and alerting - dashboards, metrics collection, slow query analysis, and proactive capacity alerts.
Enable new capabilities - deploying and tuning vector databases for AI workloads, evaluating new database technologies.
Collaborate with Data Platform, Data Engineering, Engineering, and Security teams on database operations and best practices.
Uphold database SLAs that support retrieval paths, feature stores, and embedding durability; coordinate safe schema evolution, partitioning, and replay/backfill practices.
Expose catalog and lineage signals - ownership, change history, and impact analysis - to improve trust and safe consumption for downstream users.
Collaborate with Data Platform, Data Engineering, Engineering, Security, Product, AI/ML, Data Science, and Analytics to balance performance, durability, and evolution across workloads.

It starts with you - an engineer driven to build resilient, automated infrastructure that enables teams to move fast with confidence. You care about operational excellence, developer experience, and reliability at scale. Youll architect and operate the compute and networking infrastructure that powers our AI platform - from CI/CD pipelines to Kubernetes clusters to observability systems - across cloud and on-prem environments.
If you want to build infrastructure that powers mission-critical AI systems at national scale, join mission - this role is for you.
:Responsibilities
Architect and operate Kubernetes-based infrastructure across AWS and on-prem environments, ensuring high availability, security, and performance.
Design and maintain CI/CD pipelines for application and service deployments with automated testing, security scanning, and rollback capabilities.
Drive infrastructure-as-code practices for compute and networking - building reproducible, auditable, and version-controlled infrastructure.
Own reliability and incident response - establish SLOs, build alerting systems, lead incident resolution, and drive post-incident improvements.
Enable AI-native operations - support agentic deployment pipelines, self-healing infrastructure, and secure sandboxing for model experimentation.
Build and maintain observability systems - metrics, logging, tracing, and dashboards that provide visibility into system health.
Optimize infrastructure cost and performance - right-size resources, implement auto-scaling, and identify efficiency opportunities.
Collaborate with Engineering, Data Platform, Data Engineering, and Security teams to align infrastructure with platform needs.
Shape infrastructure characteristics that support data freshness, correctness, and low-latency pathways for AI training/inference, retrieval, and agentic workflows.
Contribute paved-road tooling - reusable CI/CD patterns for services, IaC modules for compute and networking, and runbooks - that streamline delivery across teams.
Collaborate with Engineering, Data Platform, Data Engineering, Security, Product, AI/ML, Data Science, and Analytics to anticipate and meet cross-functional needs.

It starts with you - a senior ML engineer responsible for building, training, evaluating, and operating machine learning systems in production. The role focuses on data pipelines, model training, experimentation, evaluation, and scalable deployment.
If you want to grow your skills building AI products for mission-critical AI, join mission - this role is for you.
:Responsibilities
Design, train, and evaluate ML models for production use.
Build and maintain data pipelines for training, validation, and inference.
Own experimentation workflows: feature engineering, training runs, and comparison.
Implement model evals, monitoring, and drift detection.
Package and deploy models to production systems.
Optimize training and inference performance, cost, and reliability.
Collaborate with data, platform, and product teams.
Mentor engineers and promote ML engineering best practices.

we are looking for a Senior NLP Researcher.
:Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

We are on an expedition to find Technical Delivery Engineer, someone who is passionate about creating intuitive, out-of-this-world In this role, you will lead end-to-end implementation and deployment projects of platform in customer environments, working hands-on with AI on-prem and hybrid infrastructures.
Youll collaborate closely with Product, Architecture, and R&D teams, while serving as a trusted technical partner for customers and senior stakeholders. From planning and execution to troubleshooting and continuous improvement, you will own the full delivery lifecycle and ensure every deployment is reliable, seamless, and impactful.
:Responsibilities
Lead end-to-end project delivery in close collaboration with Product, Architecture, R&D, and Solutions teams, as well as customer executives and senior stakeholders.
Plan, coordinate, and execute complex on-premises deployment projects.
Take a hands-on role in deploying platform within customer environments.
Serve as the technical escalation point for issues related to product deployment and implementation.
Develop, maintain, and continuously improve project delivery processes and knowledge-sharing practices.
Communicate project status, milestones, risks, and dependencies clearly to internal teams and customer stakeholders, ensuring transparency and alignment throughout the delivery lifecycle.

We are looking for a Technical Presale Engineer with a strong technical orientation in cyber security and networking.
The ideal candidate has 2-4 years of customer-facing experience (e.g., presales, solutionarchitects, technical account managers, training, or consulting), and a willingness to travel.
The role is ideal for people who combine strong technical knowledge with an energetic attitude and the ability to build strong client relationships.
:Responsibilities
We are looking for a Technical Presale Engineer with a strong technical orientation in
cyber security and networking. The ideal candidate has 2-4 years of customer-facing experience (e.g., presales, solutionarchitects, technical account managers, training, or consulting), and a willingness to travel.
The role is ideal for people who combine strong technical knowledge with an energetic attitude and the ability to build strong client relationships.
You will help execute technical presales processes and contribute as a trusted client advisor, ensuring successful solution delivery and long-term customer satisfaction.
We work in a high-paced environment, with frequently changing priorities. Hence a high degree of flexibility and adaptability is required.

We are seeking an experienced DevOps Team Leader to lead our DevOps team as part of our Platform Engineering group. As a DevOps Team Leader, you will be responsible for overseeing the design, development, and deployment of our sophisticated DevOps solutions across cloud and on-premises environments. This role involves leading a team of DevOps engineers, driving best practices in code, architecture, and infrastructure management while ensuring high availability and optimal performance of our services.
:Responsibilities
Lead and mentor a team of DevOps engineers in building and maintaining the best solutions for our production platform.
Champion an 'Everything as Code' approach: manage our infrastructure using a wide range of technologies including Ansible, Terraform, and Kubernetes.
Oversee the creation and maintenance of tools for automation, deployment, monitoring, and operations.
Drive troubleshooting and resolution of issues in our development, production, and test environments.
Foster a culture of excellent communication, collaboration, and innovation within the team.
Ensure continuous professional development and upskilling of team members to keep pace with technological advancements.

We are on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building Sensor.
This team owns the entire endpoint agent, which is the backbone of collection capabilities from Windows and Linux endpoints.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the agent that enables our fully AI-driven platform to identify and respond to real-time advanced persistent threats.
: Responsibilities
Lead a team responsible for the endpoint product on Windows and Linux systems.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and code production-grade C++ to create robust and high-performance software applications.
Collaborate with backend, frontend, research and other teams within the company to deliver state-of-the-art solutions for challenging problems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.
Participate in code reviews with an emphasis on design and code quality, ensuring the team adheres to best practices and guidelines.

Were on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building the AI application foundation behind our next-generation cyber-AI product.
This team owns the core backend and frontend infrastructure that powers all user-facing applications - as well as the agentic and conversational frameworks that bring intelligence and automation into the experience.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the systems that enable every other Engineering group to create fast, scalable, and intelligent apps on top of our platform.
:Responsibilities
Lead a multidisciplinary team responsible for backend services, frontend frameworks, and AI agent infrastructure - the technical bedrock of our product experience.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and build robust frameworks and systems that power all customer-facing applications.
Develop the agentic and conversational architecture enabling LLM-powered user interactions and intelligent workflows.
Collaborate with AI research, data, and product teams to seamlessly integrate AI-driven capabilities into production systems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.

In this role, you'll be responsible for designing and implementing evaluation, validation and optimization of GenAI systems. You will define, design and develop LLMs as judges to evaluate task and system outputs across multiple applications, create datasets for benchmarking and evaluation and help design robust and scalable evaluation pipelines for both onine and offline GenAI systems.
:Responsibilities
Design, develop and apply state-of-the-art techniques for evaluating and validating AI agents and/or workflows.
Develop and implement LLM-as-a-Judge (or similar) for different tasks and roles for GenAI systems and tools.
Design and implement evaluation pipelines and benchmark datasets for evaluating model quality, relevance and system consistency for various applications.
Optimize and maintain judge LLMs to evaluate outputs for different use cases such as chatbots, RAG systems, cybersecurity experts and investigators.
Define evaluation KPIs and metrics for both models, systems and tools.
Validate and optimize datasets for various use cases.
Ensure the reliability, efficiency, and scalability of evaluation tools and pipelines for both online and offline use cases.
Work closely with AI/ML engineers to make evaluations a part of the production pipelines of GenAI applications.
Collaborate with cross-functional teams including product, research and data science.
Stay up to date with the latest developments in AI, machine learning, focusing on LLMs, exploring how emerging technologies can be applied to improve our evaluation and validation pipelines.

We are on an expedition to find you, someone who is passionate about creating intuitive, out-of-this-world execution and delivery. You will own the squads delivery and processes reporting directly to the Director of Program Management, collaborate with Engineering, Data Science, Research and Product teams to drive successful execution of squad deliverables.
:Responsibilities
Lead and manage multiple squads, ensuring efficient workflow and high-quality output
Partner with the Product Manager and R&D Manager to oversee the end-to-end development process for our cybersecurity solutions
Collaborate with the Director of Program Management to align squad goals with overall company objectives
Foster a culture of innovation, continuous improvement, and technical excellence
Mentor and develop team members, providing guidance and support as needed
Implement and optimize agile methodologies to enhance team performance and product delivery

Were on the lookup for a senior backend engineer to join our Detection group. Be a significant part of the development of infrastructure that efficiently handles, processes, and stores vast volumes of data. Architect and build scalable, high-performance backend system that enables real-time threat detection platform and find state-sponsored attacks.
: Responsibilities
Design and develop complex, large-scale backend systems that efficiently handle, process, and store high volumes of data.
Translate business and technical requirements into clear backend architecture and detailed implementation plans, with strong focus on design quality, maintainability, reliability, and performance.
Collaborate closely with cross-functional teams (Product, Data, DevOps, Security) to deliver robust backend and data-processing capabilities.
Build resilient, production-grade systems and drive modern engineering practices, leveraging cloud technologies.
Debug and resolve complex backend issues using strong analytical and problem-solving skills.
Lead processes, drive initiatives end-to-end, and contribute to a collaborative, positive team culture.

Were building the next generation of autonomous cybersecurity technology - systems that think like attackers to continuously uncover security gaps in enterprise environments.
As a Senior Engineer in our Attack Simulation Platform team, youll design and build the engines, data models, and intelligent agents that simulate advanced adversaries across large-scale networks. Youll combine strong software-engineering skills with deep security intuition to create systems that mirror human attacker behaviour and discover real weaknesses before attackers do.
:Responsibilities
Design and build AI-driven agents that emulate adversarial behaviours such as lateral movement, privilege escalation, and persistence.
Develop core simulation and orchestration components in Go (primary language) and integrate with in-house AI models.
Model and simulate attack paths across complex enterprise environments (identity, endpoint, network, and cloud).
Collaborate with red-teamers, researchers, and data scientists to translate threat intelligence and real attack TTPs into executable logic.
Contribute to architecture decisions, scalability, and performance optimization for distributed simulations.

We're building Cyber Threat Intelligence platform - an AI-first product that harvests, contextualizes, and serves threat intelligence at scale. We're looking for a Python-native backend engineer to own the infrastructure that makes this possible.
You'll design and build the systems that power both agentic AI workloads and large-scale data orchestration - exposing CTI insights as a service to UI components, APIs, and autonomous agents across the ecosystem. This is a greenfield opportunity where you'll shape foundational architecture decisions on a new product with a small, high-impact team.
:Responsibilities
Shape and build our data lake architecture, orchestration layer, and data access patterns.
Build the tooling and infrastructure that enables AI agents to consume and reason over threat data.
Develop systems that harvest data from open and dark web sources, cross-reference signals, and contextualize raw intelligence into actionable insights.
Serve curated CTI data to various consumers - dashboards, internal services, and other agents in the platform.
Instrument complex workflows with tracing and metrics - when things break in production, we need visibility to understand why.
Create developer tooling and experiences that make the platform usable for other engineers building on top of it.