We're looking for an Infrastructure Engineer to go deep into that layer: build and own core proxy and networking infrastructure, not configure someone else's.

You bring the same range as our core infrastructure engineers - proxies and networking, browser internals, and cloud-native systems (Kubernetes, Docker, AWS) - with the depth to design and debug at every layer of the stack, plus a genuine specialization in networking and proxy systems.

What Youll be Doing:
Build core proxy infrastructure - reverse proxies, IP rotation, session management, intelligent routing.
Own IP pool health - reputation scoring, monitoring, blacklist recovery - across residential, mobile, datacenter, and ISP proxies.
Implement geo-targeting at country, city, and ASN level.
Work at the protocol level (TCP/UDP, sockets, HTTP/HTTPS/SOCKS5, HTTP/2/3) and the Linux networking stack underneath.
Build monitoring, health checks, failover, and bandwidth/usage metering for the proxy fleet.
Deploy and scale on cloud-native infrastructure (Kubernetes, Docker, Terraform).
Use AI-assisted development tools daily.

We need a Director to set the strategy for everything underneath it - cloud, security, and the delivery lifecycle - and to bring AI into how that infrastructure is run.

This is a director-level leadership role, not an IC stretch assignment. You will lead our DevOps organization - which already has a team leader running day-to-day delivery - and operate one level up: setting direction, owning the roadmap, making architecture and build-vs-buy calls with authority, and representing infrastructure at the leadership table. Close enough to the work to guide it in depth, senior enough to own it end to end.

What Youll be Doing:
Own cloud infrastructure and security as one strategy: architecture, scale, and the path to our next order of magnitude of growth, with our security and compliance posture (IAM, secrets, hardened baselines, SOC 2 / ISO 27001 audit readiness) built in from the start, not bolted on.
Own the SDLC end to end, and drive AI into every stage of it: measure delivery performance (lead time, deployment frequency, change failure rate) and use AI to improve each stage of the lifecycle - planning, code review, testing, release, and operations - alongside AIOps practices like automated/self-healing recovery and intelligent alerting.
Own FinOps as a strategic discipline: the cloud bill is a P&L line you're accountable for, with unit economics driven down every quarter.
Own vendor and contractual relationships across cloud, tooling, and infrastructure services - negotiating leverage, not just approving invoices.
Lead the DevOps organization through its team leader: set technical direction and standards, develop the team leader into a stronger manager, and grow the bench beneath them.
Partner as a peer with Backend, Infra, AI, Data, Product, Security and Finance leadership - infrastructure decisions get made with you in the room, not after.

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 infrastructure-someone 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 stacks-its 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 lakes-designed 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 store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

As a Senior DevOps Engineer, youll help turn agentic AI capabilities for diagnosing and troubleshooting network and GPU infrastructure into secure, scalable, production-ready services. This role stands out through its end-to-end ownership across cloud and customer-managed environments, close partnership with software and AI engineers, and direct influence on the reliability of NVIDIAs AI infrastructure.


What You'll Be Doing:
Own the DevOps, infrastructure, security, release, and reliability lifecycle - from development environments and CI/CD through deployment, production readiness, and sustained operations.
Build and operate Kubernetes environments and Helm-based deployments for a Python, FastAPI, Node.js, and React microservices platform across SaaS and on-premises footprints.
Engineer GitLab CI/CD pipelines with automated testing, container builds, vulnerability scanning, and versioned image and Helm chart publication through JFrog Artifactory.
Automate infrastructure provisioning, configuration, upgrades, and routine operational workflows to accelerate delivery and improve engineering productivity.
Operate PostgreSQL, Temporal workflow services, and S3-compatible object storage with disciplined capacity planning, backups, recovery testing, and safe migrations.
Strengthen release reliability through deployment validation, reduced-downtime strategies, persistent-state protection, and recovery plans for active workflows.
Deliver actionable observability and security using OpenTelemetry, Datadog/Grafana, Langfuse, secrets management, identity integration, TLS, Kubernetes RBAC, network policies, and container hardening.
Partner with software and AI engineers to troubleshoot distributed systems, investigate incidents, define reliability targets, and improve platform performance, resource efficiency, and customer outcomes.

We are on a mission to secure the AI transformation that every company is going through, building a platform that protects organizations as they adopt AI tools at scale. This is your chance to join one of the fastest-growing areas in our company and develop technology that will define how cybersecurity operates in the AI era. You will be part of a multidisciplinary team of backend engineers, endpoint developers, AI researchers, and product experts from Israel and global acquisitions, all working together to deliver cutting-edge, end-to-end security solutions to the worlds largest enterprises.
As a Software Developer on our team, you will work across both backend services and endpoint components, designing scalable systems that connect endpoint-level data collection with cloud-based analysis and enforcement. Youll play a key role in building the agents and services that monitor and control interactions with AI tools, shaping a new category of security products that operate seamlessly across platforms and environments.
Key Responsibilities
Develop and maintain backend services alongside endpoint components for a cross-platform security platform
Design scalable systems that integrate endpoint-collected data with cloud-based processing and enforcement
Build and enhance endpoint agents responsible for monitoring and controlling interactions with AI tools (e.g., coding assistants, web-based AI services)
Implement data pipelines, policy enforcement logic, and secure data handling mechanisms across endpoint and backend layers
Collaborate with AI and product teams to deliver end-to-end solutions
Troubleshoot and resolve complex issues across distributed system and endpoint components.

What You'll Actually Be Doing
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).

We are on a mission to secure the AI transformation that every company is going through, and the OS level agent is at the heart of that mission. This is your chance to join the fastest growing area in our company and build technology that will shape how cybersecurity works in the AI era. You will be part of a multi disciplinary team that includes AI researchers, cloud engineers, and OS experts from Israel and from acquisitions like Lakera, all working together to deliver cutting edge solutions to the largest customers in the world.
Build a macOS security product that protects enterprises from AI-related threats by monitoring interactions with generative AI services across browsers and development tools. Work with a multi-process system architecture featuring network interception, real-time policy enforcement, and deep macOS integration.
Key Responsibilities
Collaborate with Windows, Backend, QA, Product Management and AI teams to ensure consistent behavior and protection across platforms
Develop new features in Swift and maintain existing Objective-C codebase
Build LaunchDaemons/LaunchAgents with XPC-based inter-process communication
Contribute to the network proxy infrastructure for network traffic interception
Leverage Apples system facilities to provide optimal Security
Integrate with IDEs and implement MCP protocol proxying
Manage and orchestrate proxy services deployed at runtime
Debug complex multi-process security software.

We are looking for a detail-oriented and technically skilled Senior QA Engineer to join our engineering team and help ensure the quality, reliability, and security of our product.
In this role, you will own the quality of complex cybersecurity features from design through production, working closely with developers, product managers, and automation engineers. You will play a key role in defining test strategies, identifying risks early, and ensuring high-quality releases.
As part of your daily workflow, you will leverage AI-powered tools to improve test planning, discover edge cases, investigate defects, analyze logs, and enhance overall testing efficiency.
Responsibilities
Own the automation domain end-to-end: strategy, architecture, implementation, and continuous improvement
Design, build, and maintain scalable test automation frameworks across UI, API, integration, and system layers
Develop hands-on automation code in Python and/or TypeScript
Drive quality standards across engineering teams, partnering closely with developers, QA, DevOps, and product stakeholders
Define and implement automation best practices for reliability, scalability, maintainability, and fast feedback
Integrate and optimize automation within CI/CD pipelines to enable rapid, confident releases
Test complex SaaS, cloud, and cyber-related product flows, including security-sensitive scenarios, permissions, integrations, and system behavior
Use AI tools to support automation development, test generation, debugging, log analysis, documentation, and coverage improvement
Proactively identify coverage gaps and improve system testability, observability, and debuggability
Participate in system design and feature planning to embed quality from the earliest stages
Build and evolve testing environments using scripting, infrastructure-as-code, and cloud-native tools
Mentor and guide engineers, elevating automation standards across the organization.

Every millisecond and every bit per second matter when you're defending the world's largest networks. We're looking for a passionate Performance Engineering Manager to lead our performance lab - an effort that spans both development and testing. This isn't only about finding where the product breaks. It's about making our products faster, leveraging and improving our AI infrastructure, and making both our products and our testing dramatically more efficient and robust.
You'll lead a team of QA and R&D engineers who design and build the tests, run them, dig into the numbers and the product, and turn what they find into concrete optimization work with development. If you love pushing the limits as much as you love finding the bug that's costing you those limits, this is your role.
Key Responsibilities
Lead and grow a team of QA and R&D engineers covering both performance development and performance testing
Set the technical direction for performance testing methodology, standards, and best practices across the lab, spanning both hardware and software projects
Leverage our existing AI infrastructure to make the lab more efficient - faster test cycles, faster analysis, faster answers, and ultimately faster, more optimized products
Go beyond identifying regressions: analyze results and actively propose performance optimizations to development teams
Increase visibility into performance results across R&D and product leadership, with clear, accessible reporting and dashboards
Own the performance strategy for our product lines, from planning and development through execution and reporting
Push traffic generator platforms to their limits to simulate real-world network and application traffic at scale
Partner with R&D, product management, and architecture teams to define what "great performance" means for our customers
Chase down performance bottlenecks at the system, kernel, and network level, and work directly with engineering to fix them
Build and maintain lab infrastructure, tooling, and automation to keep the lab sharp and scalable.