לוח משרות דרושים ארכיטקט מערכת תוכנה בנתניה, לחיפוש זה נמצאו 4 משרות

As Chief Architect, you will lead cross-group technical efforts, head the Architect Guild, and lead the department's AI enablement and transformation efforts. You will serve as a technical consultant and see the large picture of technology stack and its architecture. Our technology stack is built to handle significant complexity, integrating advanced AI, Data Science, and algorithmic optimization with robust infrastructure - ranging from cloud-native K8s and Serverless deployments to specialized Mobile and Embedded systems

This is not a docs and slides position, were looking for an architect who wishes and can stay hands-on and be able to dive into multidisciplinary complex issues and independently solve them. You will work closely with R&D leads and engineers to ensure engineering best practices and excellence.

We're a leading force in the ad tech industry, revolutionizing how brands connect with their audiences. Our platform processes billions of ad impressions daily, generating massive datasets that drive our core business.

We thrive on innovation and seek a Senior Data Infra Engineer to help us build and scale the data infrastructure that powers our insights and analytics.
This is a unique opportunity to work with cutting-edge technologies and make a direct impact on our products.

What will you do?
As a Senior Data Infra Engineer, you'll be a key part of our data platform team, responsible for designing, building, and maintaining robust and scalable data pipelines. You'll work closely with data scientists, analysts, and server side engineers to ensure our data is reliable, accessible, and ready for analysis. Your expertise will be crucial in expanding our data warehouse and data lake capabilities, enabling us to deliver next-generation ad tech solutions.

Your mission will be to:

Develop and Optimize Data Pipelines: Design, build, and maintain ETL/ELT pipelines using Apache Spark to ingest, process, and transform large-scale datasets from various sources.
Manage Cloud Infrastructure: Architect and manage our data infrastructure primarily on Google Cloud Platform (GCP) or Amazon Web Services (AWS). This includes services like BigQuery, S3, GCS, EMR, and AirFlow.
Enhance Data Storage: Improve and manage our data warehouse and data lake solutions, ensuring data quality, consistency, and accessibility for business intelligence and machine learning applications.
Collaborate and Innovate: Partner with cross-functional teams to understand data needs and implement solutions that support new product features and business initiatives.
Ensure Data Integrity: Implement monitoring, alerting, and logging systems to maintain data pipeline health and ensure data accuracy.

CTO AI Lab Architect
About the Lab
We manage the software supply chain for 80% of the Fortune 100 - packages, container images, ML models, agent skills, MCP servers, and AI-generated code. The rules are changing fast, and we need someone who can build the next generation of tools to manage, govern, and secure it all.
Our CTO Lab is a small, senior team building what comes next. We sit across the entire platform - Artifactory, Xray, Curation, AppTrust, ML, AI Catalog, Fly, Runtime, Distribution - and our job is to figure out how AI changes all of it. We run focused experiments, prototype fast, demo often, and grow what works into products alongside our product and engineering groups.
This role has two modes. In Build mode, you'll work across the full breadth of the platform - from artifact management and security to ML lifecycle and developer experience. In Scout mode, you'll be our antenna - evaluating new AI frameworks as they drop, scanning for emerging patterns in agentic AI, supply chain attacks, and developer tooling, and feeding evidence into our strategic decisions.
As a CTO Lab Architect you will build:
AI-powered supply chain intelligence - LLM systems that reason over artifacts, dependencies, and release signals to move past static block/allow rules toward decisions a senior engineer would make.
Agent systems and governance - build and secure AI agents that operate against registries, pipelines, and deployment systems. Extend our controls to the AI artifact stack we ship today - MCP Registry, Agent Skills Registry, AI Catalog - and design the next generation of governance models.
AI woven across the platform - versioning, security, and provenance for AI artifacts, and capabilities that make developers faster wherever speed, trust, or judgment can be amplified.
Evaluation and measurement - benchmarks and pipelines that prove AI-powered approaches actually outperform traditional ones. Data beats opinions.
Technology scouting and signal analysis - evaluate new AI frameworks and security innovations as they emerge. Concise assessments of what's real, what's hype, and what it means for us.