דרושים » הנדסה » Staff Engineer, Data Products

we are looking for a Senior Software Engineer to join our Core Engineering group. The group is responsible for the real-time, low-latency infrastructure that powers fraud decisions and external APIs.

Our systems process billions of requests every day, ensuring high availability, security, and performance at global scale.

In this role, youll work on core backend components such as our decision engine, ingestion and enrichment pipelines, schema management systems, and self-serve API platform. The software you build will power critical business decisions and directly serve some of the worlds largest merchants.

This is a high-impact, high-ownership position for an engineer who thrives on solving complex distributed systems challenges, cares deeply about production-grade quality, and wants to shape the foundation of decisioning platform.



What you'll be doing:

Design, build, and scale backend systems that power real-time decisioning and APIs.
Own projects end-to-end - from design and implementation to production rollout and monitoring.
Ensure systems are low-latency, fault-tolerant, and high-throughput across distributed environments.
Enhance observability, reliability, and developer experience through strong operational and tooling practices.
Collaborate with Product, analysts, data scientists, and infrastructure teams to drive innovation across decision ecosystem.
Participate in technical discussions and customer interactions, providing expertise and clear communication when supporting enterprise integrations.

We are rebuilding the way chips get built, and were looking for a senior engineer to help lead that transformation.

This is a full-stack platform role on the team responsible for the development environment behind our silicon. You will help define how agentic orchestration and durable execution become first-class parts of the chip-design workflow.

Were looking for someone who has built complex systems before - across backend, frontend, and infrastructure - and is ready to set the technical direction for what comes next.

What You'll be doing:

Architect and lead full-stack EDA platforms end to end, from data models and backend services to the frontends engineers use every day - while making key technical and build-vs-buy decisions.

Own the infrastructure these platforms run on at scale, including CI/CD, containerization, observability, on-prem compute, and cloud-native Kubernetes environments.

Set engineering standards across the team by leading design reviews, improving reliability and developer experience, and mentoring engineers.

Act as a technical leader across silicon, backend, and design-automation teams, helping turn fragile manual flows into dependable automated systems used by many engineers.

we are looking for a DevOps Engineer.
our DevOps team operates the infrastructure that powers our AI and Computer Vision platform across construction sites in 15+ countries. From data pipelines and ML workloads to backend services - you'll work with a diverse, modern, Kubernetes-based stack and have real influence on how we build, deploy, and operate.
What you'll do:
Own Multi-Cloud Infrastructure: Work alongside the team to design, scale, and operate our high-scale, multi-region production infrastructure across AWS and GCP, powering construction sites globally.
Drive Kubernetes at Scale: Manage and evolve our Kubernetes platform on EKS and leveraging GitOps practices with ArgoCD and Helm to enable safe, fast, and reliable deployments.
Build Robust CI/CD: Design and maintain CI/CD pipelines that empower dozens of engineers to ship confidently - with automation, testing, and progressive delivery built in.
Tackle Diverse Infrastructure Challenges: Work hands-on with a wide variety of workloads - from heavy data processing and Computer Vision pipelines to backend services and ML inference - each with unique scaling, performance, and reliability requirements.
Ensure Reliability & Observability: Build and maintain world-class observability (metrics, logs, tracing, alerting) so that issues are caught early and resolved fast. Performance, reliability, and scalability are at the core of what you do.
Security & Cost: Partner with the team to strengthen our security posture, identity and access management, compliance, and cloud cost optimization across both clouds.
Ownership from 0 to 1: You will have real influence over our architecture and tooling. We want engineers who care about shaping what we build and how we build it, ensuring performance, security, and observability are baked in from day one.

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.

We are looking for a Senior Software Engineer to join the AIOps platform team and help build the core distributed systems that ingest massive telemetry streams from GPU clusters and operationalize predictive AI models at scale. You will work at the intersection of high-performance data engineering and production ML, turning research algorithms into reliable, mission-critical software.

What you'll be doing:

Architect and build an agentic AIOps system that autonomously monitors GPU fleet health, aggregates and correlates massive telemetry streams, surfaces intelligent alerts, and orchestrates multi-step diagnostic workflows and corrective actions - powering real-time dashboards, automated root-cause analysis, and proactive incident response.

Research, evaluate, and prototype data storage strategies and data representations across diverse database technologies and modalities, ensuring AI models are trained on high-quality, well-structured data that improves predictive accuracy and generalization.

High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.

Instrument services with deep observability (metrics, logs, traces) to support rapid debugging and continuous performance improvement.

Build and own the model-serving infrastructure that operationalizes predictive algorithms at scale - packaging, versioning, deploying, and monitoring AI models in both SaaS and on-premises environments.

Contribute to the platform's core libraries and abstractions that accelerate development across the broader AIOps engineering team.

Required Software & Data Engineer
Tel Aviv
As a Software & Data Engineer, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how we understand and improve our service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how we operate
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

Required Software Engineer
We believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, weve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.
Were a small, highly-owned team at the heart of how engineering scales. Our work is challenging to define, and thats intentional.
We own the cloud infrastructure. We manage Kubernetes clusters, continuous deployment (CD) pipelines, and shared components like Kafka and Debezium. We also provide the necessary glue to ensure the organizations production systems are reliable and self-sufficient. When tasks are manual, operational, or rely on tribal knowledge, we transform them into scalable solutions, such as services, operators, or shared libraries. Our approach is production-first. We prioritize shipping products that must survive, scale, and improve over time with minimal intervention.
Responsibilities:
Youll transform operational tasks, currently residing in runbooks, Slack threads, and minds, into robust, observable, and maintainable systems. This involves:
Designing and constructing Kubernetes operators and infrastructure microservices that enable self-healing and self-management of the infrastructure.
End-to-end ownership of shared infrastructure components like Kafka and Debezium, facilitating safe and independent consumption by the rest of the R&D team.
Developing continuous delivery (CD) pipelines and deployment workflows that minimize time-to-deliver and eliminate bottlenecks between teams.
Designing systems with self-service in mind, allowing other teams to expedite their processes without initiating tickets.
Measuring key performance indicators (KPIs) such as ticket volume, hours of manual work per week, time-to-deliver, and the level of friction experienced by consumers.
This transformation goes beyond automation through scripting languages like Python or Bash. It demands genuine software engineering expertise, encompassing API design, extensibility, failure modes, observability, and upgrade paths.

At our company, "It's all about the user. All of them." We're passionate about providing a seamless one-stop experience for business travelers, no matter how they travel, where they stay, or where they're going. we are building cutting-edge solutions at the intersection of travel, expense, payments, and AI. As a leader in the AI for Travel domain, we are using intelligent, practical AI experiences to make business travel simpler, faster, and more reliable for travelers, travel managers, finance teams, and support teams.
We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep our company reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.
This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.
This position is based out of our new Tel Aviv office.
What You'll Do:
Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.