We are seeking a seasoned Backend Developer with a solid background in high-load environments and experience in managing multiple Linux servers. The ideal candidate is someone who thrives in a fast-paced, innovative, and technology-driven culture.
Responsibilities:
Own architecture for high-scale, user-facing backends and data pipelines.
Lead and mentor engineers; guide design reviews, roadmaps, and execution.
Operate production systems with clear SLOs/SLAs, on-call quality, and blameless postmortems.
Evolve our K8s/GPU platform, CI/CD, and observability to increase deployment velocity and resilience.
Integrate and serve ML models (PyTorch, CUDA/TensorRT, Triton) with a focus on throughput and cost.
Partner cross-functionally (ML, Product, Security, Finance) on priorities and cost/perf trade-offs.
Hire, level up the team, and uplevel engineering standards.

We are seeking a seasoned Backend Tech Lead with a solid background in high-load environments and experience in managing multiple Linux servers. The ideal candidate is someone who thrives in a fast-paced, innovative, and technology-driven culture.
Responsibilities:
Own architecture for high-scale, user-facing backends and data pipelines.
Lead and mentor engineers; guide design reviews, roadmaps, and execution.
Operate production systems with clear SLOs/SLAs, on-call quality, and blameless postmortems.
Evolve our K8s/GPU platform, CI/CD, and observability to increase deployment velocity and resilience.
Integrate and serve ML models (PyTorch, CUDA/TensorRT, Triton) with a focus on throughput and cost.
Partner cross-functionally (ML, Product, Security, Finance) on priorities and cost/perf trade-offs.
Hire, level up the team, and uplevel engineering standards.

We are seeking an Engineering Manager for Cloud Security Product Group.

We're extending our mission of "stopping breaches" into the public cloud and cloud-native workloads. Our product offering will give customers the ability to monitor and track their cloud-native workloads as well as hardening and protecting them against attacks prior to deployment.

This offering will help with defending against potential adversary activities involving cloud-native resources. When coupled with Falcon, our endpoint security offering, our CSPG offering will provide a more comprehensive perspective on how the adversary is targeting key customer infrastructure. Our ultimate goal is to provide a single platform for securing the entire lifecycle of cloud workloads and cloud security posture.

This role is hybrid, on-site at TLV office. Candidates should be comfortable visiting the office at least 3 times a week.


What You'll Do:

Lead, mentor and grow a team of backend engineers, driving product vision and roadmap while remaining hands-on with code and architecture.

Lead backend engineering efforts from rapid prototypes to large-scale applications across our products.

Leverage and build cloud-based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale.

Balance hands-on technical contributions with people management responsibilities.

Brainstorm, define and build collaboratively with members across multiple teams.

Drive technical direction and make architectural decisions for the team.

Work in a startup-like environment with a small fast-moving team.

Mentor and be mentored by other developers on backend, and data storage technologies and our system.

Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability.

Be given the autonomy to own your work in a high trust environment.

The Agentless Scanning team is expanding our security platforms capabilities by delivering comprehensive cloud protection that complements our industry-leading agent technology. Weve evolved from pioneering Data Security Posture Management (DSPM) to building a unified agentless platform that combines data security with vulnerability scanning, providing complete visibility across multi-cloud environments.

Our technology scans cloud workloads, identifies vulnerabilities, and secures sensitive data across AWS, Azure, and GCP - extending our protection to cover every aspect of your cloud infrastructure. Were solving some of the most challenging problems in cloud security: how to provide deep visibility and protection at scale across diverse cloud services and configurations.

Were a team of builders and innovators who thrive on complex technical challenges. If youre energized by distributed systems, cloud-native architectures, and the opportunity to protect thousands of organizations worldwide, we want to hear from you.

Join us in expanding our security platform, where innovation meets impact.

What Youll Do:

Architect and build scalable backend services that scan millions of cloud resources daily across multi-cloud environments.

Design and implement distributed systems that process massive volumes of security data with high reliability and low latency.

Develop agentless scanning capabilities for vulnerability detection, configuration assessment, and data security across cloud workloads.

Collaborate cross-functionally with security researchers, product managers, and fellow engineers to deliver features that customers love.

Own features end-to-end - from design and implementation through deployment, monitoring, and iteration.

Drive technical excellence through code reviews, architectural discussions, and mentoring team members.

Solve complex challenges in cloud security, data processing, and distributed systems at enterprise scale.

We are seeking We are seeking an experienced Senior Generative AI Engineer (LLMs & Agents) to join our AI squad at KPMG. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work.
You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms.
You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities:
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Pytho
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliability, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS
Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.)
Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques
Define and refine best practices for GenAI system development and deployment
Contribute to internal accelerators, methodologies, and knowledge sharing

Were hiring a Machine Learning Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across Stamplis B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.

This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.

What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of ML engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across our products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

Required xEngineer (ai-native software engineer)
makes it possible for anyone to succeed online. since 2006, weve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. here, we push you to innovate, evolve in non-traditional ways, and collaborate. we operate in small teams that work closely together at a high level.
although were already industry leaders in web creation and business, our work is nowhere near done. our goal is to become the main engine of the internet so we can create a more open web for all.
we're proud to be an equal opportunity employer. the company was built around the idea that everyone has the right to be successful, online. this same vision defines us as an employer: creating a work environment where everyone is welcome, and anyone has the right to succeed.
as an xEngineer, youll combine deep technical expertise with system -level thinking and product ownership, applying ai across the development lifecycle to build impactful systems, make thoughtful architectural decisions, and drive technical excellence from idea to production. in your day-to-day, you will:
design and own end-to-end systems and features that serve millions of users, taking responsibility across stack boundaries - from product flows and User Experience to apis, data models, and production systems
apply ai-powered tools and workflows across planning, design, implementation, testing, debugging, and refactoring
work with modern technologies and platforms (e.g., typescript, React, Node.js, JAVA, cloud, and ci/cd), continuously evolving your toolkit with ai-powered tools
lead architectural thinking by making thoughtful trade-offs around scalability, reliability, security, performance, and maintainability
collaborate closely with product managers, designers, and engineers to shape solutions while ensuring production quality, observability, and long-term system health
at the company, we believe our best work happens together. our work model is fully in person, with 5 days a week from our office. flexibility remains a core value at the company and special requests are handled thoughtfully at the team level.
we are engineering at the company - a team of ai-native xengineers with deep expertise in frontend, backend, or mobile, who use ai support to take ownership over projects end-to-end. we work in a fast-paced, dynamic development environment with autonomous teams that never compromise high quality standards. as ai increasingly generates production code, we dedicate more and more of our time developing the skills we believe are critical for today and tomorrow: system design, architecture, scalability, reliability, and security.

We are seeking a Senior Engineer for Cloud Security Product Group.

Were extending our mission of stopping breaches into the public cloud and cloud-native workloads. Our product offering will give customers the ability to monitor and track their cloud-native workloads as well as hardening and protecting them against attacks prior to deployment. This offering will help with defending against potential adversary activities involving cloud-native resources. When coupled with Falcon, our endpoint security offering, our CSPG offering will provide a more comprehensive perspective on how the adversary is targeting key customer infrastructure. Our ultimate goal is to provide a single platform for securing the entire lifecycle of cloud workloads and cloud security posture.

What You'll Do:

Lead backend engineering efforts from rapid prototypes to large-scale applications across our products.

Leverage and build cloud-based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale.

Brainstorm, define and build collaboratively with members across multiple teams.

Work in a startup-like environment with a small fast-moving team.

Be mentored and mentor other developers on backend, and data storage technologies and our system.

Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability.

Be given the autonomy to own your work in a high trust environment.

Required Backend Software Developer
Israel: Tel Aviv/ Hybrid (Israel)
R&D | Full Time | Job Id: 25310
Why Join Us?
We are building the automation backbone that powers development.
As part of the I/S Group, our team provides the core infrastructure for building, running, and analyzing code quality and automated tests across our products. We design and maintain scalable pipelines, frameworks, and tools that developers and QA engineers rely on every day to ship secure, high quality software faster and with confidence.
We are looking for a developer who enjoys designing robust automation systems, streamlining developer workflows, and making our build and test processes faster and more transparent.
Key Responsibilities:
Design, build, and maintain robust automation infrastructure and services that serve as the backbone of engineering operations.
Develop AI-driven tools and features that empower automation users and elevate developer workflows across the organization.
Enhance and extend existing automation services used by developers across.

Were looking for an Engineering Team Lead, who will be responsible for the foundational infrastructure framework used by all engineering teams to build, deploy, and operate AI agents safely in production. We are building the "operating system" for AI , covering agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. You will lead a high-impact team of 3-4 engineers to create the runtime and platform that defines the future of autonomous enterprise intelligence.
Youll Own:
Agentic Framework Architecture: Designing and building internal agentic framework, leveraging and integrating industry-standard tools such as LangChain, LangSmith, ADK, and similar ecosystems.
Evaluation and Quality Systems: Building evaluation frameworks and workflows for AI agents, including offline and online evaluations, quality metrics, regression detection, and experimentation infrastructure.
Team Leadership & Mentorship: Leading a squad of 3-4 senior engineers, fostering a culture of technical excellence, and managing end-to-end delivery in a fast-paced environment. You will spend approximately 50% of your time hands-on, architecting core systems and reviewing code, and 50% leading the team, mentoring engineers, and aligning with cross-functional stakeholders.
Observability, Monitoring, and Guardrails: Providing the organization with robust observability capabilities for AI agents, including tracing, logging, monitoring, cost tracking, and safety guardrails to ensure reliable and responsible usage.
Developer Enablement Platforms: Creating APIs, SDKs, and abstractions that enable product teams to easily build, test, and operate agents while adhering to platform standards.
Cross-Language Integrations: Designing integrations and tooling across Python and Java to enable seamless adoption of the AI framework within broader backend ecosystem.
Youll Solve:
Agent Lifecycle and Orchestration Complexity: Managing agent execution, tool usage, memory, workflows, and failure modes in production-grade systems.
AI System Reliability at Scale: Ensuring agents remain observable, debuggable, and safe as usage scales across teams and products.
Evaluation and Drift Challenges: Detecting quality regressions, model behavior changes, and unintended agent behaviors through robust evaluation and monitoring systems.
Platform Adoption Friction: Balancing flexibility with guardrails so teams can innovate quickly without compromising reliability, security, or cost controls.