דרושים » תוכנה » Infrastructure Software Engineer

We are seeking a passionate and highly skilled Senior Golang Developer to join our dynamic Software Engineering team. The ideal candidate is an expert Go engineer with a strong background in building scalable, high-performance distributed backend systems on the cloud. You should be enthusiastic about working with cutting-edge technologies in an Agile environment and capable of owning complex components end-to-end, taking an idea through design, testing, and production monitoring.

What will you do:
Responsible for the full lifecycle of our distributed services, focusing on performance, reliability, and innovation: Design & Development
* Architect, design, and implement robust backend services and distributed system components using Go, ensuring high scalability, reliability, and performance.
* Develop microservices and server side infrastructure with clean, maintainable, and testable code.
* System Ownership: Take full ownership of complex components, moving them from initial concept design through development, testing, CI/CD, and production deployment and monitoring. System Optimization & Data
* Optimize service performance, parallel processing, concurrency handling, and resource utilization in high-scale environments.
* Work with a variety of data stores and event-streaming technologies.
* Integrate services with technologies like OpenSearch, Redis, and column store databases as part of the system architecture.
* Implement secure development practices and production ready standards. Collaboration & DevOps
* Work closely with Data Engineering, DevOps, and Product teams to deliver high quality, production grade services.
* Develop and deploy applications in Kubernetes environments, leveraging strong DevOps best practices and CI/CD pipelines for smooth, reliable releases.
* Participate actively in code reviews, design discussions, and cross team technical initiatives. Innovation
* Explore new technologies, evaluate tools, and propose improvements to the existing stack and development processes, championing a culture of continuous improvement and technical excellence.


About Us:
Cynet is a leader in threat detection and response, designed to simplify security for organizations of all sizes. Our mission is to empower lean security teams and their partners with an AI-powered, unified platform that autonomously detects, protects, and responds to threats - backed by 24×7 security experts. With a Partner First mindset , we focus on helping customers and partners stay protected, operate confidently, and achieve their goals. Our vision is to give every organization true cybersecurity peace of mind, providing fast, accurate protection without the noise or complexity.

We are looking for a Tech Lead, Infra.
What You'll Do:
Creating and deploying core software infrastructure components at scale.
Maintaining and enhancing our internal Typescript frameworks, tools, and platforms essential for product engineering teams throughout the software development lifecycle.
Introducing self-service deployment capabilities to empower R&D teams.
Advocating for and enforcing standards and best practices.
Leading and educating through knowledge sharing via documentation, knowledge-base articles, blogs, forums and presentations.
Addressing complex production issues and developing long-term solutions.
Contributing to the engineering and standardization of our CI/CD infrastructure.
Working closely with cross-functional teams to ensure the targeted availability, reliability, scalability, throughput and performance of our infrastructure while adhering to industry best practices and standards.

We are seeking a highly skilled Senior Networking AI Platform Engineer to join our Applied Networking AI group. In this role, you will help design and develop cutting-edge AI solutions, integrating them seamlessly into a variety of products. Youll collaborate closely with multi-functional teams of data scientists, software engineers, and DevOps professionals to ensure the efficient deployment, monitoring, and optimization of machine learning (ML) models.
As a key contributor, you will drive the entire software development lifecycle-from conceptualization and architecture to implementation and production-while working closely with engineering teams to solve complex problems and help build a successful company practice.
What you'll be doing:
Lead the design, development, and deployment of robust software systems across different platforms and environments
Architect, design, and implement scalable and high-performance software solutions, handling complex requirements and integrating various subsystems
Ensure systems are maintainable, flexible, and well-documented, with an emphasis on performance and security
Adapt to new tools, technologies, and frameworks, and be capable of taking ownership of the development process from conception to deployment
Supply innovative ideas and solutions, driving continuous improvement in both code quality and system efficiency
Develop and maintain scalable infrastructure for handling and deploying security and networking ML models in production, ensuring high availability, scalability, performance.
Design and implement data pipelines to efficiently process and transform large volumes of data for training and inference purposes.
Optimize and fine-tune ML models for performance, scalability, and resource utilization, considering factors such as latency, efficiency, and cost.
Collaborate with data scientists and software engineers to operationalize and deploy ML models, including model versioning, packaging, and integration with existing systems.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructuresomeone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacksits about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakesdesigned for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object storebacked data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

As a Lead DevOps Engineer, your role involves the design and development of robust, scalable, and resilient distributed systems. You'll define product specifications, leveraging your technical expertise to create optimal solutions hosted in Kubernetes on AWS Cloud. This position requires extensive collaboration with various teams throughout the software development lifecycle. You will lead design discussions and code reviews, contributing to the overall quality of engineering within the organization.

Your responsibilities also include creating and supporting reusable application components and patterns, considering both business and technology perspectives. You'll utilize developer tools and a range of AWS services for task management, source code handling, building, deployment, operations, and real-time communication. You are expected to demonstrate advanced skills in application design, implementation, and maintenance, often with minimal supervision.

Beyond technical tasks, you will mentor other engineers, sharing your knowledge and actively contributing to the enhancement of best practices and processes within and across teams.

Responsibilities:

Design, build, and maintain the scalable cloud infrastructure and CI/CD pipelines necessary to support our cutting-edge AI and optimization services.

Champion Infrastructure as Code (IaC) practices using tools like Terraform and Kubernetes to automate the deployment, scaling, and management of our production environments.

Implement robust monitoring, logging, and alerting systems to ensure the high availability, performance, and reliability of all services.

Partner with development teams to streamline the software development lifecycle, improve deployment velocity, and embed best practices for security and operational excellence.


JR314438

Required Software Engineer
Your Role: Drive, Build, and Shape
Build Scalable Solutions: Develop a robust, scalable system using a mix of languages, frameworks, and machine learning models. Youll take full ownership of features, guiding them from idea to live product.
Customer-Centric Development: Collaborate directly with customers to understand their needs and integrate valuable insights into your work.
Cross-Disciplinary Innovation: Engage in initiatives across various tech domains - from DevOps and infrastructure to data engineering and full-stack development - expanding your impact company-wide.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of Lemonades data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives Lemonade toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.

In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams

Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights

Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance

Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights

Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions

Collaborate closely with other Staff Engineers across Lemonade to align on cross-organizational initiatives and technical strategies

Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions

Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization

We are looking for a Team Lead to join our Network Orchestration group. Our group is responsible for developing scalable, high-performance distributed systems that support complex network infrastructures.
As a Team Leader, you will drive the architecture, design, and development of critical components of the system. You will lead a team of frontend engineers, define best practices, and ensure the scalability and maintainability of the system
Our group is growing, and you will play a key role in building and expanding the team. You'll have the opportunity to optimize and enhance key parts of our system, leveraging the latest tools and infrastructure to drive innovation and efficiency.
Responsibilities
Lead & mentor a high-performing development team in building advanced, scalable software solutions.
Collaborate closely with development teams to provide seamless integration across applications.
Work closely with QA to implement best practices for testing and automation, ensuring high software quality and reliability.
Coordinate with Product Managers to align development with business priorities and roadmap planning.
Engage with UI/UX Designers to ensure an intuitive and high-quality user experience.
Define and enforce best practices, coding standards, and architectural guidelines for frontend development.
Stay updated with industry trends and emerging technologies to drive innovation in UI infrastructures.
Work with CI/CD pipelines to automate testing, deployment, and monitoring of UI libraries.

Run:ai, now part of our company, has evolved AI infrastructure by merging GPU virtualization with Kubernetes-native capabilities. Our world class AI platform allows organizations to improve productivity and efficiency for data scientists and machine learning engineers. With deep Kubernetes expertise and a focus on innovation, we are dedicated to developing groundbreaking technologies. We deliver the best user experience for our customers and provide detailed access to workload performance through rich metrics. These metrics help users optimize their AI workloads. We are looking for highly skilled Devops engineers to join our Infrastructure Group and help shape the future of AI infrastructure.
What you'll be doing:
Take full end-to-end ownership of our cloud infrastructure, spanning development environments to production systems across various cloud platforms.
Compose, build, and develop the architecture of Run:AI cloud-native products for a variety of complex customer environments, including on-premise, and cloud
Identify and fix production issues while addressing performance challenges to ensure our systems operate flawlessly.
Collaborate closely with cross-functional groups to provide architectural and infrastructure input that builds product direction and composition.
Partner with R&D, Customer Success, Professional Services, and Pre-sales teams.
Continuously evaluate and implement new tools and technologies to improve our release and product deployment processes.

We're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-driven technology, representing the pinnacle of Machine Learning, GenAI, and computer vision within the automotive sector. With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, we stand at the forefront of automotive technological advancement. Our growing global team of over 200 employees is committed to creating a workplace that celebrates diversity and encourages teamwork. Our drive for innovation and pursuit of excellence are deeply Embedded in our vibrant company culture, ensuring that each individual's efforts are recognized and valued as we unite to build a safer automotive world.
We are seeking a highly motivated and skilled Release Manager to join our AIOps group. In this role, you'll play a critical part in bridging the gap between development and operations, ensuring the seamless qualification, deployment, and monitoring of our AI algorithms and infrastructure, and be responsible for the end-to-end operationalization of our core technology.
A day in the life and how youll make an impact:
* Manage a team of 3 release engineers.
* Manage the end-to-end release process of Machine Learning algorithms and infrastructure components, from qualification through deployment.
* Validate and TEST new algorithm releases to ensure they meet performance, stability, and compliance standards.
* Create and execute deployment plans across various environments (staging, production), ensuring minimal risk and downtime.
* Collaborate closely with AI researchers, MLOps, and software engineers to understand release requirements, share feedback, and resolve pre-release issues.
* Identify and drive automation opportunities within the release pipeline to improve efficiency, reliability, and traceability.
* Oversee updates to infrastructure components, ensuring compatibility and performance across systems.
* Monitor deployments, proactively identify issues related to model behavior or infrastructure anomalies, and drive resolution with relevant teams.
* Maintain clear and accurate release documentation, including version history, deployment notes, and incident reports.