דרושים » תוכנה » Software Engineer, Systems

We are seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
Software Engineer, Product Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding.

As a Senior/ Principal/ Senior Principal Software Engineer at Cortex Cloud, you will serve as a primary technical architect and visionary for our core communication infrastructure. This role is focused on the critical server-side backbone that facilitates high-scale bidirectional communication between our cloud services and client-side applications.
You will be responsible for the architectural integrity of systems that receive massive data inflows from the field and reliably broadcast intelligence back to millions of endpoints. This is a high-impact leadership role requiring a blend of deep technical mastery in distributed systems and the ability to influence technical strategy across the organization.
Key Responsibilities
Architectural Strategy & Vision: Define and drive the multi-year technical roadmap for our server-side communication infrastructure, ensuring the platform remains resilient and performant under extreme load.
High-Scale Communication Infrastructure: Lead the design and implementation of backend systems optimized for receiving high-scale data from client-side apps and distributing data back to a vast ecosystem of endpoints.
Technical Leadership & Influence: Act as a force multiplier by providing technical guidance to multiple engineering teams, aligning them on shared protocols, architectural standards, and communication patterns.
Drive Engineering Excellence: Champion a culture of high engineering rigor, focusing on deep observability, low-latency data distribution, and runtime stability for mission-critical production environments.
Cross-Functional Collaboration: Partner with Product Management, Infrastructure, and Client-Side Engineering teams to evaluate technical trade-offs, mitigate risks, and ensure seamless end-to-end data flow.
Innovation & Prototyping: Spearhead the evaluation of emerging technologies and lead "proof of concept" initiatives for next-generation transport layers and messaging paradigms.
Technical Mentorship: Invest in the growth of Senior and Staff engineers through deep-dive design reviews, code audits, and hands-on pair programming on the most critical paths.
Strategic Customer Engagement: Support the business by leading technical deep dives with strategic customers, translating complex architectural concepts into actionable confidence for our partners.

We are looking for a Technical Lead to drive the architectural direction and engineering excellence of this group. This is a senior, deeply hands-on role for a technology leader who can own the technical roadmap, mentor a team of elite engineers, and build the infrastructure that challenges platform to its theoretical limits.
What You'll Lead:
Define and own the technical architecture of the group's distributed testing and reliability platform - designing for massive scale, real-world workload simulation, and adversarial failure injection
Lead effort involving multiple engineers, setting technical standards, running architecture reviews, driving design decisions, and mentoring engineers to grow
Build the systems that orchestrate millions of concurrent IO operations, inject chaos at the infrastructure layer (latency, packet loss, hardware failures), and expose the hardest-to-find race conditions and consistency bugs
Advance AI-driven approaches to test automation: intelligent scenario generation, LLM-augmented root-cause analysis, and autonomous validation pipelines
Drive observability and reliability engineering across the group - building telemetry pipelines that track P99 latency, jitter, and system health, turning quality into a quantitative discipline
Collaborate deeply with Core R&D, Storage Kernel, and Infrastructure teams - translating architectural knowledge into targeted reliability strategies
Establish engineering practices - design docs, production-grade code reviews, testing philosophy, and cross-team technical alignment

We're seeking a Staff engineer - AI Builder to lead the design and implementation of AI-native technical frameworks that redefine how large-scale systems are built, extended, and evolved.

This role is deeply technical and architecture-driven, focused on designing modular, extensible, and AI-first system foundations that enable scalable development with AI as a core engineering collaborator.

You will work across the full stack, building infrastructure where AI actively generates, extends, and maintains software components as part of the native development flow.

This is not about incremental AI integration - this is about architecting the frameworks that let AI scale software engineering 10x faster and smarter.

Responsibilities:
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Build platform primitives that enable dynamic AI-driven module and extension generation.
Design and implement developer workflows optimized for AI-assisted software development, embedding AI collaboration as a first-class design principle.
Define and codify AI-native engineering practices, patterns, and guidelines to elevate our software development lifecycle.
Establish and champion best practices for AI-assisted engineering across system design, code quality, testing, observability, and operational scalability.
Drive hands-on prototyping and iterative delivery across frontend, backend, and orchestration layers.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Partner closely with Product, AI, and Engineering teams to align system evolution with AI-native goals.

You will be working on core B2B platform that serves tens of thousands of customers, serving hundreds of terabytes in production. Our backend engineers are responsible for the entire data lifecycle - from our endless datatlakes, through choosing the right serving methods and databases, all the way to our api services.

So, what will you be doing all day?

Design and implement scalable backend services and libraries that are reusable and maintainable, serving as the foundation for various applications across the company.
Build and maintain tools that streamline development workflows, enabling product teams to focus on delivering business value.
Define and promote best practices for code quality, performance, and reliability, ensuring healthy production environments and rapid development cycles.
Lead the adoption and integration of AI tools to assist in code generation, testing, documentation, and debugging, thereby accelerating development processes.
Perform proof-of-concepts (POCs) on emerging technologies, including AI agents and platforms, to assess their applicability and benefits to our development ecosystem.
Drive cross-team technical projects aimed at improving infrastructure scalability, reliability, and developer experience.
Analyze and resolve complex production issues, ensuring minimal downtime and optimal performance.
Contribute to the evolution of our system architecture, ensuring it supports rapid development and scaling needs.

As a Backend Software Engineering, your job responsibilities will include:
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
Make design decisions on the basis of performance, scalability, and future expansion.
Work in a Hybrid Engineering model and contribute to all phases of SDLC including design, implementation, code reviews, automation, and testing of the features.
Build efficient components/algorithms on a microservice multi-tenant SaaS cloud environment
Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level).

At our company, we build AI-powered vision systems that enhance safety and decision-making for some of the worlds largest vessels.
Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency.
Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions.
This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.
This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.
What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server)
Take models from research and turn them into production-ready, reliable components deployed on vessels
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew)
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems
Define and maintain clear interfaces between research code and production systems
Work closely with research and backend teams to integrate new models into production systems
Continuously improve system efficiency and reliability under hardware and runtime constraints.

As a Technical Account Manager (TAM) in our Enterprise Support, you will serve as the primary technical advisor and voice of the customer for a portfolio of fast-growing Israeli startups. You will play a crucial role in fostering their innovative and transformative work across AI/ML, compute (including accelerated and GPU workloads), containers, networking, storage, databases, serverless, security, and more. It's an opportunity to work closely with technical founders and engineering leaders, helping them make the right architectural decisions at each stage of their growth journey.

Key job responsibilities
- Act as the primary technical advisor for your startup customers, building trusted-advisor relationships with CTOs, VP Engineering, and founding teams.
- Engage across the full customer organization, from individual engineers through to C-suite, adapting your communication to each audience.
- Help accelerate customer growth by crafting strategies that balance startup velocity with Well-Architected best practices across AI/ML, compute, containers, and data infrastructure.
- Conduct architecture reviews, operational assessments, and proactive risk identification. Analyze service events and operational patterns to drive continuous improvement in resilience, performance, and cost efficiency.
- Drive technical discussions with founding teams on architecture trade-offs, incident response, and risk management as their systems scale.
- Uplift customer capabilities by running workshops, enablement sessions, and brown bag sessions tailored to their technical needs.
- Champion and advocate for your customers by connecting their feedback to our engineering teams, influencing platform evolution, and ensuring rapid resolution of concerns.
- Collaborate with Solutions Architects, Business Developers, Professional Services, and Account Managers to deliver coordinated customer value.
- Develop and share technical content such as blog posts, reference architectures, and reusable solutions that help startups solve common challenges and reduce time-to-market.

Were looking for a Staff Engineer to lead the design and development of central components within R&D.
Youll combine hands-on development with architectural leadership - solving complex engineering challenges, guiding your team through design decisions, and ensuring our systems are robust, scalable, and maintainable.
Youll collaborate with other senior engineers, tech leads, and product partners to define technical direction, drive innovation, and improve engineering practices across the teams and groups.
This is a role for someone who thrives on building well-designed systems, driving technical excellence within the team and mentoring peers
Responsibilities:
Lead the design and implementation of scalable and reliable backend services.
Drive architectural discussions and make key technical decisions within your domain.
Collaborate with cross-functional teams to translate business and product goals into technical solutions.
Deliver high-quality, maintainable, and testable code while ensuring best practices for security, performance, and reliability.
Mentor and support engineers through design reviews, code reviews, and knowledge sharing.
Continuously improve development processes, observability, and deployment pipelines.
Contribute to the evolution of the platforms architecture as the company and product scale.

We are seeking an AI Networking Architect to join the Networking Research Group. This role will help bridge the gap between emerging tasks supported by advanced technologies and the data center infrastructure that powers them. In this role, you will work at the intersection of AI applications, distributed systems, networking hardware, and software architecture.

You will join a focused team of multidisciplinary engineers driving AI workload optimization through deep application understanding, network analysis, and end-to-end systems thinking. Your insights will directly shape our products across the full stack - from applications and software libraries to hardware architecture and physical design.

What Youll Be Doing:

Model the performance of complex AI workloads to identify bottlenecks and recommend system-level optimizations.

Analyze brand-new AI models, distributed training techniques, and inference workloads to understand their infrastructure requirements.

Build Platforms, simulations and HW platforms, execute AI workloads and build analytical tools to evaluate trade-offs across compute, memory, storage, and network behavior.

Translate research insights and workload behavior into actionable software, hardware, and networking architecture requirements.

Partner with architecture, software, and product teams to influence our future networking and AI infrastructure roadmaps.

Drive architectural innovation by applying deep workload analysis to real-world advanced machine learning frameworks.