The Collab Unit is looking for an exceptional Team Leader to lead the Audience Team. The Audience Team is responsible for building the products and infrastructure that enable customers to create, manage, and activate high-value audiences across multiple channels and marketing use cases. This is a strategic domain at the heart of how customers derive value from behavioral data.
As the team leader, you will manage a multidisciplinary engineering team and help shape the future of audience building and activation. You will work closely with product, architecture, data, and other engineering teams to deliver scalable, reliable, and user-centric solutions. This role requires a strong engineering leader who is passionate about building excellent teams, solving complex data and backend challenges, and driving execution in a fast-moving environment.
What Youll Do:
Lead and grow a high-performing engineering team responsible for end-to-end ownership of audience-related products and capabilities
Drive the design and delivery of scalable backend systems and data flows that power audience creation, enrichment, segmentation, and activation
Partner closely with Product, Design, Architecture, and cross-functional engineering teams to define and execute the team roadmap
Translate product and business goals into clear technical plans and ensure predictable, iterative delivery
Stay hands-on and involved in architecture discussions, design reviews, and code reviews
Foster a strong engineering culture of ownership, collaboration, quality, and continuous improvement
Mentor and develop engineers, supporting their professional growth and helping them reach their full potential
Recruit top talent and build a healthy, balanced, and effective team
Ensure high production standards, operational excellence, and system reliability
Promote curiosity and technical excellence by evaluating new tools, technologies, and approaches where relevant
Take an active role in shaping the broader engineering direction of the Collab Unit together with fellow team leaders

We are looking for an R&D Group Lead to take ownership of the SaasLab group - leading multiple engineering teams responsible for the core platform services that every product depends on. You will drive the technical vision and execution or architectural transformation while ensuring the reliability and scalability of SaaS foundation.
The position requires a strong architectural mindset, experience leading platform and infrastructure-level work, and the ability to balance long-term technical strategy with continuous delivery of business value.
What youll do:
Lead and mentor a group of engineers and team leads across multiple domains (core entities, access & API gateway, billing & integrations), fostering growth in design, architecture, and people leadership
Own the SaaS platform end to end - ensuring high availability, security, and operational excellence of the systems that underpin every product
Drive and execute an architectural transformation: decoupling from legacy data stores, building a resilient domain model, and adopting modern patterns like GraphQL Federation
Work closely with product managers and cross-functional stakeholders, taking accountability for group deliveries and ensuring teams ship on time with excellent quality
Lead technical initiatives, processes, methodologies, and architectural decisions across the group
Drive AI Products development, SDLC and process improvements via cutting edge tools and methodologies
Be a meaningful and major member of AFOS leadership team and influence the units engineering vision, processes, and culture

We are seeking a skilled and motivated Software Engineer (Automation Infrastructure) to join our team. This role is primarily focused on designing, developing, and maintaining robust automation frameworks and ensuring seamless integration with external systems and partner teams. The ideal candidate will have a strong background in infrastructure automation, excellent problem-solving skills, and a collaborative mindset.
Responsibilities
Design, build, and maintain efficient and reliable automation frameworks.
Implement, test, and bug-fix automation scripts and tools.
Write clean, scalable, and testable code for infrastructure automation.
Participate as a team member in fully agile Scrum deliveries.
Coordinate with other software professionals and developers.
Provide support to end users for automation tools and frameworks.
Collaborate with external teams and third-party vendors to implement integration solutions.
Remain up to date with the terminology, concepts, and best practices in infrastructure automation.

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

Were expanding our Data & AI group and looking for a passionate, experienced Senior Data & AI Engineerto join our mission. This is a unique opportunity to work at the intersection of data engineering, LLMpowered systems, agentic workflows, and cybersecurity innovation

What youll work on
Data Infrastructure & EngineeringDesign, build, and scale production-grade data pipelines using Databricks, Spark, and modern cloud-nativetechnologies. Ensure high standards of data integrity, system performance, reliability, and scalability.
Core Backend & PlatformDesign and contribute to scalable backend services and platform capabilities using microservices andevent-driven architectures. Build reliable APIs, integrations, and asynchronous data flows that support highscale AI, data, and cybersecurity use cases.
LLM & Agentic SystemsDesign, prototype, and integrate LLM-powered systems, including Retrieval-Augmented Generationpipelines, agentic workflows, tool-using agents, multi-step reasoning flows, and AI-driven automation. Workwith technologies such as AWS Bedrock, OpenAI, Anthropic, LangGraph, vector databases, and modernorchestration frameworks.
AI-Assisted Engineering & Developer ProductivityExplore and apply advanced AI coding assistants and software-engineering agents, such as Codex andClaude Code, to improve development velocity, code quality, debugging, testing, and experimentation.Build proof-of-concepts and internal tools that help engineering and research teams work more effectivelywith AI-powered development workflows.
Intelligent Cybersecurity FeaturesCollaborate with Security Researchers, Engineers, and Product teams to identify opportunities forintelligent, data-driven features that deliver actionable cybersecurity insights to customers. Transformcomplex cybersecurity and platform data into reliable, explainable, and useful AI-powered capabilities.

we are looking for a Senior Data Engineer to join our Data Platform team. We are seeking a hands-on individual with experience in building and scaling modern data infrastructure, passionate about exploring AI technologies and applying them to enhance and evolve our data systems. This role is ideal for someone focused on data systems, performance, automation, and reliability, who will design, build, and maintain core components of our data pipelines, storage, monitoring, and observability stack, with a strong focus on improving workflows and system capabilities, while embracing the Shift4 way.

Responsibilities:

Build and maintain scalable, reliable, and high-performance data infrastructure across cloud and on-prem environments
Partner with engineering, analytics, and observability teams to support data flow from ingestion to consumption
Develop infrastructure as code and automation tools to improve deployment, monitoring, and recovery
Help troubleshoot performance bottlenecks and reliability issues in large-scale data pipelines
Implement data quality processes aligned with security standards to ensure accuracy, consistency, and compliance with financial regulations and PCI requirements.
Continuously improve the performance and efficiency of the data platform with proactive tuning and benchmarking
Proactively explore and apply AI tools to enhance efficiency across the data engineering lifecycle, while improving accessibility and usability of data solutions for teams across the organization

We are looking for a Senior DevOps Engineer with deep expertise in cloud-native platforms to join our global DevOps group and help shape the future of our next-generation SaaS platform
Responsibilities
Collaborate across global R&D teams to manage and evolve a complex, Azure-based production environment powering a cutting-edge data security SaaS platform. 
Build and maintain scalable, resilient, and highly available cloud infrastructure using DevOps practices. 
Design and implement CI/CD pipelines, GitOps workflows, and infrastructure automation using tools like Terraform, Pulumi, Argo CD, and Azure DevOps. 
Work closely with R&D teams to design, implement, and support new product features across the platform. 
Evaluate and adopt emerging cloud-native technologies, open-source tools, and observability platforms to enhance system performance and developer productivity. 
Respond to incidents and internal requests, performing triage, root cause analysis, and implementing solutions to reduce recurrence and resolution time. 
Participate in a 24/7 On-Call rotation to proactively monitor and resolve production issues, ensuring platform stability. 

Play a part in shaping the future of human-computer interaction. As an MLOps Engineer, you will be the backbone of the machine learning infrastructure that powers our speech, audio, and conversational AI teams - ensuring their models are trained on the best possible data.
You will bridge the gap between research, data science, and engineering, owning the full ML lifecycle from large-scale data pipelines and distributed GPU training through to low-latency, high-fidelity inference and optimization. You'll partner closely with Audio ML Engineers, Speech ML Engineers, and ML Data Scientists to remove friction across their workflows and accelerate the path from research to product.

The MLOps Engineer will drive end-to-end quality and operational excellence across data ingestion, model training, deployment pipelines, and MLOps tooling for our speech and audio ML platforms. This hire will build, deploy, and optimize production-grade systems with a strong emphasis on scalable, GPU-accelerated infrastructure. You will own the training infrastructure that powers distributed and self-supervised model training on HPC and Slurm-managed clusters, as well as the inference pipelines that bring low-latency, high-fidelity audio and speech models to production. You will establish standard methodologies for model integration, deployment, monitoring, and reproducibility using CI/CD principles.

Responsibilities
Design, build, and operate large-scale data pipelines for proprietary audio and speech datasets - supporting curation, quality monitoring, and validation at scale alongside our ML Data Science team.
Partner closely with Audio ML Engineers, Speech ML Engineers, ML Data Scientists, and product teams to define metrics, gather requirements, and bring new capabilities to life.
Build and operate distributed GPU training workflows, including job scheduling and resource management on Slurm-managed HPC clusters, for both supervised and self-supervised methods.
Optimize model inference for low latency and high-fidelity streaming across serving environments, including optimization for Apple silicon.
Design and maintain automated pipelines for model training, evaluation, versioning, and deployment, with special attention to speech, audio, and signal-processing workflows.
Identify and resolve bottlenecks in ML and data workflows, improving system reliability, latency, and throughput at scale.

We have multiple positions open for Full stack Software Engineers and Senior Full stack Software Engineers to be hired across different Security teams in Israel.

As a Software Engineer you will:
Contribute to business-critical initiatives in our Security.
Use deep technical skills and the ability to quickly adapt to new areas.
Improve the end-to-end lifecycle of services.
Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.
Work on high-end technologies and collaborating across disciplines to deliver impactful features.
Collaborate with multiple teams across us to deliver key customer solutions and support technology.

A self-motivated automation engineer with strong programming fundamentals, responsible for designing, writing, and maintaining automated tests across software, firmware, backend, frontend, and mobile - while owning the full automation infrastructure and CI pipeline.

You will design, write, and maintain automated tests covering backend services, frontend interfaces, and mobile applications, including software and firmware. You will own and evolve the automation infrastructure, the physical lab environment, test agents, and CI pipeline reliability, while collaborating closely with development engineers to build and run automated test suites, triage failures, and expand coverage as new features are introduced. Industry best practices such as POM (Page Object Model) and AAA (Arrange-Act-Assert) patterns will guide your work to ensure automation projects remain well-structured, maintainable, and scalable. Over time, you will deepen your product knowledge to broaden test suite coverage accordingly, contribute to internal tooling, and leverage generative AI tools to improve productivity across test development, documentation, triage, and reporting.

Responsibilities
Test automation framework design and development (Python, Pytest, Playwright).
Backend, frontend, and mobile test automation across multiple platforms, including iOS/macOS using XCTest.
Applying automation best practices: POM, AAA, and scalable project architecture.
Debugging and troubleshooting hardware and software issues.
CI/CD pipeline configuration and maintenance.
Lab infrastructure management.