דרושים » תוכנה » Software Engineer, Interceptor Systems

Hands-on software engineering for our cutting-edge missile interceptor system. You'll develop and integrate components across the software stack, either on the Embedded / flight side (RTOS, low-latency sensor and comm code on the interceptor) or on the ground station / Command & Control side (distributed services for mission monitoring, threat evaluation, and visualization). You'll work under the Software Group Lead's architectural direction, with deep ownership of the modules you ship. We are looking for a "builder" mentality, someone who drives end-to-end delivery from concept to field deployment, and who treats AI coding tools as a force multiplier rather than a curiosity.
Why Join us?:
This is a unique opportunity to be at the heart of a defense-tech startup during its most exciting growth phase!
Responsibilities:
Build: Develop flight software, sensor fusion algorithms, and secure communication protocols between the interceptor and C2; or build distributed microservices for the ground station, depending on which area fits your background. Integrate: Work alongside Hardware Engineering (mechanical, electrical, GNC), Systems Engineering, and Program Management to integrate the software with the rest of the missile and ground station. TEST : Participate in HIL/SIL testing phases, support field trials, and write the automation that keeps these tests fast and reliable. AI-assisted delivery: Use modern AI coding tools (GitHub Copilot, Cursor, Claude Code, etc.) heavily across your daily work to ship faster without compromising safety-critical standards. Collaborate: Contribute to design reviews and architectural decisions; raise issues and propose alternatives rather than waiting for direction.

we are looking for a MLOps Engineer.
As an MLOps Engineer, you will work at the intersection of backend engineering and machine learning, building the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features used by hundreds of thousands of families.
What you'll be doing -
Build Production AI Systems - Design and implement backend services and end-to-end AI solutions that integrate Deep Learning models, Computer Vision algorithms, and GenAI into real features.
Power Experimentation and Validation - Contribute to the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Develop Data Pipelines - Build and maintain scalable data pipelines and big-data solutions that feed AI capabilities reliably and with an eye on cost and scale.
Own What You Ship - Take features end-to-end within your squad, from planning and design through implementation, deployment, and monitoring in production.
Cross-functional Collaboration - Work closely with the Algorithms and Data teams to tackle complex, real-world problems, helping translate research into shippable, maintainable systems.
Backend Guild Engagement - Actively contribute to a backend guild that drives Software Engineering and System Design best practices, guidelines, and standards across the R&D team.

we are looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:

We are seeking a highly skilled and innovative Control Engineer to join our dynamic team dedicated to advancing the field of autonomous vehicles. As a Control Engineer, you will play a crucial role in designing, developing, implementing and testing hands on control algorithms to enhance the performance, safety, and efficiency of our autonomous vehicle systems.
please note that this position requires 2 days a week at our HQ in Jerusalem
What will your job look like?
Work on developing and optimizing control algorithms for the vehicle
Run and analyze simulations to test autonomous vehicle in virtual environments
Collaborate with hardware engineers to integrate control algorithms with the vehicle's hardware components, such as sensors, actuators, and onboard computers
Working with communication protocols and interfaces for both internal and external communications with different components of the system
Customer facing workshops to discuss and test your algorithms.
Testing your algorithms in an Autonomous vehicle.

Required Software Engineer III, Infrastructure, Chronicle SOAR
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
To enhance the reliability, performance, and security of Chronicle Security Orchestration, Automation and Response (SOAR) through innovative software engineering. We build, automate, and maintain the systems and tools that ensure Chronicle SOAR operates at scale, transforming operational challenges into robust, software-driven solutions in close partnership with product development teams.
Responsibilities
Design, build, and maintain software and systems that enhance the reliability, availability, and performance of Chronicle SOAR.
Create and improve software tools, platforms, and services that automate complex operational workflows, reduce manual toil, and improve the efficiency of managing Chronicle SOAR at scale.
Develop and manage infrastructure configurations and policies using Go to ensure secure, consistent, and auditable management of GCP resources for Chronicle SOAR.
Design and implement sophisticated monitoring, logging, and tracing solutions.
Analyze past incidents and proactively develop software solutions to prevent recurrence. Build automation to accelerate incident detection, diagnosis and resolution, and contribute to blameless post-mortems to identify and implement systemic improvements.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

Required Software Engineer III, Platform Engineering and Infrastructure
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a part of this team, you will join the premier engineering powerhouse driving Chronicle Security Orchestration, Automation and Response (SOAR) to operate at true scale. As hyper-focused experts in Platform Engineering and Infrastructure, the team holds absolute ownership over the Security Operation provisioning service, orchestrating complex resources in our Cloud Platform and mission-critical workloads in Kubernetes (GKE) and in Compute infrastructure with precision. You do not simply respond to operational issues, but build the platforms, tools, and developer infrastructure that transform complex challenges into robust, software-driven solutions.
Responsibilities
Write product or system development code.
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

We are a fast-growing cybersecurity startup redefining how organizations protect themselves. Our Data Team is at the heart of that mission - powering everything from security insights to customer-facing intelligence. We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

You will build globally distributed, fault-tolerant, and highly scalable identity threat detection systems that analyze billions of authentication events per day to detect sophisticated Active Directory attacks, credential theft, and lateral movement across hybrid and multi-cloud (Azure/Entra, Okta, AWS) environments. You'll design, lead, and implement the next generation of our Identity Protection detection platform - evolving it from on-prem appliances toward cloud-native, event-streaming microservices.

What You'll Do

Design and implement real-time detection rules and pipelines over high-throughput Kafka event streams, maintaining sub-second detection latency at massive scale.

Build the pluggable detection engine and rule framework that turns raw authentication telemetry into indicators, and indicators into enriched, customer-facing alerts.

Develop machine-learning and behavioral-anomaly models, and integrate LLM-based detection reasoning (e.g. AI-driven severity scoring) into production detection flows.

Translate security research into production-grade detections, partnering with security researchers who guide you on the threat landscape.

Own detections in production: observability, latency SLOs, safe per-customer rollouts (feature-flag-gated), and incident response for the detection pipeline.

Work across a polyglot stack - Python for detection logic and ML, Go for the high-performance streaming services, Java for backend alert management.


This position is based in our Ramat-Gan, Israel office and requires strong leadership presence and ability to work closely with cross-functional teams.

We are looking for an ML Infra Engineer to play a central role in evaluating, and deploying our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

This is NOT a core algorithmic research role - but rather, a role focused on building out the ML engineering infrastructure for the evaluation and deployment of models.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.