Required Senior Data Engineer
About the role:
You will specialize in designing and building world class, scalable data architectures, ensuring reliable data flow and integration for groundbreaking biotechnological research. Your expertise in big data tools and pipelines will accelerate our ability to derive actionable insights from complex datasets, driving innovations in improving patients outcome and in delivering life savings treatment solutions.
In this role, you will work closely with data scientists, AI/ML engineers, architect and other cross-functional teams to understand their data needs and requirements. You will also be responsible for ensuring that data is easily accessible and can be used to support data-driven decision making.
Location: Ramat Gan, (Hybrid model)
What will you do?
Design, build, and maintain data pipelines that ingest, transform, and load noisy, heterogeneous biological data at scale - from single-cell sequencing, genomic, and clinical sources - across databases, APIs, and flat files
Enhance our data warehouse system to dynamically support multiple analytics use cases
Implement and productize complex scientific and computational algorithms as scalable, production-grade pipeline components
Drive our data infrastructure toward becoming AI-native, enabling AI/ML systems and agents to reliably query, reason over, and act on our data
Implement data governance policies and procedures to ensure data quality, security, and privacy
Collaborate with ML and AI scientists and other cross-functional teams to understand their data needs and requirements
Drive team capability growth by championing an AI-first SDLC, mentoring data engineers on AI-assisted development practices and tooling
Develop and maintain documentation for data pipelines, processes, and systems
Requirements
We will only consider senior data engineers that have demonstrated strong system design skills combined with an extensive background working with data orchestration, data warehousing and ETL tools.

we are looking for a Big Data Engineer.
As a Senior Big Data Engineer, working within Mobility Group, you will play a pivotal role in designing, developing, and maintaining the data infrastructure that powers our location analytics platform.
RESPONSIBILITIES:
Data Pipeline Architecture and Development: Design, build, and optimize robust and scalable data pipelines to process, transform, and integrate large volumes of data from various sources into our analytics platform.
Data Quality Assurance: Implement data validation, cleansing, and enrichment techniques to ensure high-quality and consistent data across the platform.
Performance Optimization: Identify performance bottlenecks and optimize data processing and storage mechanisms to enhance overall system performance and reduce latency.
Cloud Infrastructure: Work extensively with cloud-based technologies (GCP and AWS), to design and manage scalable data infrastructure.
Collaboration: Collaborate with cross-functional teams including Data Analysts, Data Scientists, Product Managers, and Software Engineers to understand requirements and deliver solutions that meet business needs.
Data Governance: Implement and enforce data governance practices, ensuring compliance with relevant regulations and best practices related to data privacy and security.
Monitoring and Maintenance: Monitor the health and performance of data pipelines, troubleshoot issues, and ensure high availability of data infrastructure.
Mentorship: Provide technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team.

We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.

Required Senior ML Data Engineer
About the team:
The AI Engineering group builds modern infrastructure and solutions that improve how algorithms are developed.
We are a small, independent team of experienced engineers with a mix of skills in algorithms, software, and infrastructure. We work in a DevOps style and build cross-team solutions that support research and development of advanced perception algorithms.
Our flagship project is a unified AV dataset used to train and evaluate next-generation models. We take large volumes of multi-camera video, object labels, HD maps, and sensor data from across the organization, and turn it into a curated, high-quality training set - at scale.
We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are seeking a Senior Software Engineer with a strong foundation in backend engineering and experience building scalable, high-performance systems.
This role focuses on designing and developing backend services that power our **AI-driven products**, with extensive work on **Large Language Models (LLMs), AI agents, and modern GenAI technologies**.
We foster a professional environment where experienced engineers collaborate to drive technical excellence and continuously improve our architecture and products. As a Senior Software Engineer, you will play a key role in building production-grade AI systems, solving complex engineering challenges around scalability, performance, reliability, and AI orchestration.
Role & Responsibilities:
* Design, develop, and optimize scalable backend services and APIs that power AI-driven products.
* Build production-grade applications and workflows using **LLMs, AI agents, and GenAI technologies**.
* Design and implement agentic workflows, including **tool calling, orchestration, context management, and integration with internal services**.
* Integrate and optimize LLM-based capabilities while balancing **quality, latency, reliability, and cost**.
* Design and maintain scalable, reliable, and high-performance distributed systems.
* Take ownership of technical solutions from design and implementation through deployment and production monitoring.
* Improve system architecture, observability, code quality, and development processes.
* Collaborate with Product, DevOps, and other engineering teams to deliver end-to-end solutions.
* Stay up to date with advancements in backend technologies and the rapidly evolving GenAI ecosystem.

we are looking for a Senior AI Software Engineer.
As a Senior AI Software Engineer, you'll help build that platform end to end - the agents, connectors, automation, and infrastructure that let the entire company unlock major productivity gains. You'll be designing and shipping AI that takes real work off people's plates, turning manual processes into automated ones, and building the systems that let teams do their best work faster.
Developing our use of Claude and Databricks - currently the backbone of that internal AI stack - is a key part of the mandate. Every one of our 500+ team members already uses Claude and BI in Databricks for analysis, automation, and research, and demand for deeper integrations is growing faster than our R&D team can deliver. You'll be tasked with driving these capabilities and impact to the next level - from surface-level usage to genuinely agentic, high-leverage workflows embedded across the business.
This is a hybrid role: part platform engineer, part internal-facing integration lead. You'll report to the COO and partner across AI Operations, R&D, Data Science, GTM, and other teams, owning the path from integration request to production-grade system. You'll also help build the triage and review process so the broader org can self-serve safely.
If you want to build the AI backbone of a fast-moving company - and see your work adopted by hundreds of people within days rather than quarters - this is that role.

Required Data Engineering Manager
Data, Ramat Gan, Israel (Hybrid)
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities:
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

Required Senior Software Engineer, Infrastructure, Cloud
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a Platform Engineer on this team, you will build, operate, and scale the mission-critical cloud infrastructure that powers Chronicle Security Orchestration, Automation and Response (SOAR) at scale. This is a heavy infrastructure operations and automation role. You will take autonomous ownership of complex operational challenges-from administering advanced Kubernetes (GKE) clusters to building sophisticated observability pipelines-ensuring the highest level of Enterprise-grade reliability and security.
You will not simply implement others' ideas, you will be expected to scope operational challenges, write robust Infrastructure as Code (IaC), and transform manual toil into software-driven platforms in close partnership with product development teams.
Responsibilities
Own all aspects of your immediate infrastructure area, leading the design and maintenance of platform tooling, deployment pipelines, and cloud systems that enhance the reliability and performance of Chronicle SOAR.
Administer, operate, and troubleshoot advanced Kubernetes (GKE) clusters and onboard new infrastructure features at scale.
Develop and manage infrastructure configurations and automation policies using Go to ensure secure, consistent, and auditable management of GCP resources.
Design and implement sophisticated monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana) and manage Service Level Objectives (SLOs)/Service Level Indicators (SLIs).
Act as a point of contact for cross-functional partners. Analyze past incidents and proactively develop software solutions to prevent recurrence. Build automation to reduce manual toil and accelerate incident resolution.

We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

We are looking for a Backend / Data Engineer to join our Core Data Pipeline team. In this role, you will be responsible for building and scaling the engine that processes our high-throughput, real-time telemetry data.
Our pipeline handles billions of events per second, performing real-time processing, data enrichment, and other transformations. If you thrive on solving high-scale, low-latency distributed systems challenges - this is the place for you.
What Youll Do:
High-Scale Engineering: Design, build, and maintain our central data processing pipeline, handling massive volumes of logs and traces at extreme scale.
Transform & Enrich: Architect real-time stream processing systems to perform complex data transformations and enrichments in real time.
Performance & Efficiency: Optimize system throughput, reduce memory footprints, and minimize latency across distributed clusters.
Architecture & Reliability: Take full ownership of feature lifecycles - from design and system architecture to production monitoring and resilience.
Our Stack:
Scala, Rust, Node.js
Kafka
Kafka Streams / Akka Streams
ClickHouse, Redis
Kubernetes
AWS.