Where these concentrations lead

A Full-Stack Software Developer builds and maintains both the client-facing interfaces and the server-side logic of web and mobile applications. They own features end to end, from database schema and API design through to the user interface, and collaborate closely with designers and product teams.

Responsibilities

Design and implement responsive front-end interfaces from UI mockups and design systems
Build and maintain REST and GraphQL APIs and the server-side business logic behind them
Model relational and non-relational database schemas and write efficient queries
Write unit, integration, and end-to-end tests and participate in code reviews
Debug production issues across the stack and ship fixes through CI/CD pipelines
Collaborate with product managers and designers in agile sprints to scope and deliver features

Required knowledge

Data structures, algorithms, and computational complexity analysis
Relational database theory, normalization, and transaction concepts
HTTP, the client-server model, and web protocol fundamentals
Object-oriented and functional programming paradigms
Software design principles such as SOLID, separation of concerns, and design patterns
Concurrency, asynchronous execution, and the event loop model

Skills

Translating product requirements into working features across the stack
Writing clean, maintainable, and well-documented code
Debugging across browser, network, and server layers
Designing and consuming APIs and managing application state
Using version control workflows and resolving merge conflicts
Optimizing front-end performance and back-end query efficiency

Tools & technologies

Example employers

WixMonday.comLightricksGoogleMicrosoftAmazonJFrogFiverr

Job role

DevOps Engineerמהנדס DevOps

A DevOps Engineer bridges development and operations by automating the build, test, and deployment pipeline and managing the infrastructure that runs applications. They focus on reliability, scalability, and fast, safe delivery of software to production.

Responsibilities

Build and maintain CI/CD pipelines that automate testing and deployment
Provision and manage cloud infrastructure using infrastructure-as-code
Configure and operate container orchestration platforms and service deployments
Set up monitoring, logging, and alerting to ensure system observability
Automate routine operational tasks with scripts and tooling
Manage secrets, access control, and environment configuration across stages

Required knowledge

Operating systems, processes, and Linux system administration concepts
Computer networking, DNS, load balancing, and TCP/IP fundamentals
Distributed systems concepts including scalability, availability, and fault tolerance
Continuous integration and continuous delivery principles
Virtualization and containerization theory
Site reliability engineering concepts such as SLOs, SLIs, and error budgets

Skills

Writing automation scripts and infrastructure-as-code definitions
Diagnosing and resolving production infrastructure incidents
Designing resilient and scalable deployment architectures
Configuring observability stacks and interpreting telemetry
Tuning system and pipeline performance
Applying security hardening to infrastructure and pipelines

Tools & technologies

Example employers

JFrogWixMonday.comAmazon Web ServicesMicrosoftGoogleCheck PointRed Hat

Job role

QA Engineerמהנדס בדיקות תוכנה (QA)

A QA Engineer ensures software quality by designing test strategies, building automated test suites, and validating that products meet functional and non-functional requirements. They work to catch defects early and prevent regressions before software reaches users.

Responsibilities

Design test plans and write detailed test cases from requirements and acceptance criteria
Build and maintain automated test suites for UI, API, and integration layers
Execute manual exploratory testing for new and complex features
Integrate automated tests into CI/CD pipelines and triage failures
Report, track, and verify defects in collaboration with developers
Perform regression, performance, and cross-browser or cross-device testing

Required knowledge

Software testing theory including unit, integration, system, and acceptance levels
Test design techniques such as equivalence partitioning and boundary value analysis
Software development lifecycle and agile methodologies
Principles of test automation and the testing pyramid
Fundamentals of HTTP, APIs, and the client-server model
Quality metrics, coverage analysis, and risk-based testing concepts

Skills

Writing clear, reproducible defect reports and test documentation
Building maintainable automated test frameworks
Analyzing requirements to identify edge cases and risks
Debugging test failures and isolating root causes
Collaborating with developers to improve testability
Designing data-driven and parameterized test scenarios

Tools & technologies

Example employers

WixMonday.comPlaytikaNICEMicrosoftAmdocsIntelFiverr

Job role

Cloud & Platform Engineerמהנדס ענן ופלטפורמה

A Cloud and Platform Engineer builds and operates the cloud foundations and internal developer platforms that other engineering teams build on top of. They design self-service infrastructure, automate provisioning, and ensure that cloud environments are secure, cost-efficient, and scalable.

Responsibilities

Design and provision cloud infrastructure across compute, storage, and networking
Build internal developer platforms and self-service tooling for engineering teams
Author and maintain infrastructure-as-code modules and reusable templates
Implement identity, access control, and network policies in the cloud
Optimize cloud spend and right-size resources for cost and performance
Operate Kubernetes clusters and platform services with high availability

Required knowledge

Cloud computing models including IaaS, PaaS, and the shared responsibility model
Distributed systems concepts such as scalability, availability, and consistency
Computer networking, DNS, load balancing, and TCP/IP fundamentals
Linux operating system internals and system administration
Containerization and orchestration theory
Infrastructure-as-code and declarative configuration principles

Skills

Designing scalable and resilient cloud architectures
Writing modular infrastructure-as-code and platform abstractions
Automating provisioning and configuration workflows
Diagnosing cloud and platform reliability incidents
Implementing cloud cost optimization and governance
Building developer-friendly self-service interfaces

Tools & technologies

Example employers

Amazon Web ServicesMicrosoftGoogleWixMonday.comJFrogSnykSalesforce

Job role

Backend Engineerמהנדס צד שרת (Backend)

A Backend Engineer designs and builds the server-side systems, APIs, and data stores that power applications behind the scenes. They focus on correctness, scalability, and performance, ensuring that services handle load reliably and integrate cleanly with other systems.

Responsibilities

Design and implement REST and GraphQL APIs and microservices
Model and optimize relational and non-relational data stores
Build asynchronous processing, queues, and event-driven workflows
Ensure service reliability, scalability, and fault tolerance under load
Write automated tests and participate in code reviews
Profile and optimize service latency, throughput, and resource usage

Required knowledge

Data structures, algorithms, and computational complexity analysis
Relational database theory, indexing, and transaction isolation
Distributed systems concepts including consistency, caching, and partitioning
Concurrency, parallelism, and asynchronous execution models
API design principles and the client-server model
Software design principles such as SOLID and design patterns

Skills

Designing clean and well-documented service APIs
Modeling data and writing efficient queries
Building scalable and resilient distributed services
Diagnosing performance bottlenecks and concurrency bugs
Implementing caching, queuing, and messaging patterns
Writing maintainable, testable server-side code

Tools & technologies

Example employers

WixMonday.comFiverrGoogleMicrosoftAmazonRiskifiedTaboola

Job role

Mobile Developerמפתח אפליקציות מובייל

A Mobile Developer builds and maintains native or cross-platform applications for iOS and Android devices. They craft responsive, performant user experiences while integrating with backend services, device hardware, and platform features.

Responsibilities

Design and implement mobile app features and user interfaces
Integrate apps with REST and GraphQL backend services
Optimize app performance, memory use, and battery consumption
Handle offline storage, caching, and state synchronization
Publish and maintain apps in the App Store and Google Play
Write tests and debug platform-specific issues across devices

Required knowledge

Data structures, algorithms, and computational complexity analysis
Mobile platform lifecycle and UI rendering models
Object-oriented and reactive programming paradigms
Concurrency, threading, and asynchronous execution on mobile
HTTP, the client-server model, and API fundamentals
Mobile security, permissions, and data storage concepts

Skills

Building responsive and accessible mobile interfaces
Integrating device features such as camera, location, and notifications
Managing app state and local persistence
Profiling and optimizing mobile performance
Debugging across device models and OS versions
Navigating app store submission and release processes

Tools & technologies

Example employers

LightricksWixGettFiverrGoogleMetaPlaytikaeToro

Concentration

Networking & Cyber Security רשתות ואבטחת סייבר

Job roles a graduate of this concentration can step into:

Job role

Network Engineerמהנדס רשתות

A Network Engineer designs, implements, and maintains the data networks that connect an organization's systems and users. They ensure secure, reliable, and high-performance connectivity across on-premises and cloud environments while defending against network-based threats.

Responsibilities

Design and configure routers, switches, firewalls, and VPN connectivity
Monitor network performance and troubleshoot connectivity and latency issues
Implement network segmentation, access control lists, and firewall rules
Plan and execute network capacity upgrades and topology changes
Document network architecture, addressing schemes, and configurations
Respond to network outages and security incidents to restore service

Required knowledge

The OSI and TCP/IP models and layer-by-layer protocol behavior
Routing and switching theory including OSPF, BGP, and VLANs
IP addressing, subnetting, and network address translation
Network security concepts including firewalls, IDS/IPS, and zero trust
Cryptography fundamentals as applied to VPNs and secure tunnels
Quality of service, congestion control, and network performance principles

Skills

Configuring and troubleshooting enterprise networking hardware
Analyzing packet captures to diagnose network problems
Designing resilient and segmented network topologies
Automating network configuration and validation
Implementing and auditing network access controls
Capacity planning and performance tuning

Tools & technologies

Example employers

Check PointCiscoPalo Alto NetworksBank HapoalimAmdocsMicrosoftIntelBezeq

Job role

DevSecOps Engineerמהנדס DevSecOps

A DevSecOps Engineer embeds security into every stage of the software delivery pipeline, automating security testing and policy enforcement alongside development and operations. They ensure that applications and infrastructure are secure by design without slowing down delivery.

Responsibilities

Integrate static, dynamic, and dependency scanning into CI/CD pipelines
Automate security policy enforcement and compliance checks as code
Harden container images, infrastructure-as-code, and cloud configurations
Manage secrets, certificates, and identity across environments
Triage and remediate vulnerabilities discovered in code and dependencies
Build threat models and security gates into the delivery workflow

Required knowledge

Application security principles and the OWASP Top Ten
Cryptography fundamentals including hashing, encryption, and key management
Secure software development lifecycle and shift-left security concepts
Identity, authentication, and authorization models such as OAuth and RBAC
Cloud security and shared responsibility models
Threat modeling and risk assessment methodologies

Skills

Automating security scanning and gating in delivery pipelines
Interpreting and prioritizing vulnerability scan results
Hardening containers, clusters, and cloud accounts
Writing policy-as-code and compliance automation
Managing secrets and credentials securely at scale
Collaborating with developers to remediate findings

Tools & technologies

Example employers

Check PointPalo Alto NetworksWizAqua SecurityJFrogMicrosoftAmazon Web ServicesCyberark

Job role

Security Analystאנליסט אבטחת מידע

A Security Analyst monitors an organization's systems for threats, investigates security incidents, and works to protect data and infrastructure from attack. They analyze alerts, hunt for intrusions, and recommend defensive improvements to reduce risk.

Responsibilities

Monitor security alerts and triage events from SIEM and detection tools
Investigate and respond to security incidents and contain threats
Conduct vulnerability assessments and track remediation
Analyze logs and network traffic to detect malicious activity
Maintain detection rules, playbooks, and incident documentation
Perform threat hunting and produce threat intelligence reports

Required knowledge

Network protocols and the TCP/IP stack as they relate to attacks
Common attack techniques and the MITRE ATT&CK framework
Cryptography fundamentals and secure communication concepts
Operating system internals and log sources on Windows and Linux
Incident response lifecycle and digital forensics principles
Risk management, threat modeling, and security governance concepts

Skills

Analyzing logs and alerts to distinguish threats from noise
Investigating incidents and reconstructing attack timelines
Writing and tuning detection rules to reduce false positives
Performing vulnerability scans and interpreting results
Communicating findings and risk clearly to stakeholders
Conducting proactive threat hunting across telemetry

Tools & technologies

Example employers

Check PointCyberArkPalo Alto NetworksBank HapoalimMicrosoftDeloitteCrowdStrikeCymulate

Job role

Penetration Testerבודק חדירוּת

A Penetration Tester simulates real-world attacks against applications, networks, and systems to find exploitable weaknesses before adversaries do. They assess security posture through hands-on testing and deliver clear reports with remediation guidance.

Responsibilities

Plan and scope penetration tests against web apps, networks, and systems
Perform reconnaissance, vulnerability discovery, and exploitation
Test for common weaknesses such as injection, broken access control, and misconfiguration
Chain vulnerabilities to demonstrate real-world impact safely
Document findings, severity, and proof-of-concept exploits
Recommend prioritized remediation and retest fixes

Required knowledge

Network protocols and the TCP/IP stack as they relate to attacks
Web application security and the OWASP Top Ten
Common attack techniques and the MITRE ATT&CK framework
Operating system internals on Windows and Linux
Cryptography fundamentals and common cryptographic weaknesses
Authentication, authorization, and access control models

Skills

Identifying and exploiting vulnerabilities in a controlled manner
Performing reconnaissance and attack surface mapping
Writing and adapting exploit scripts and payloads
Assessing and prioritizing risk by business impact
Producing clear, actionable penetration test reports
Communicating findings to technical and non-technical audiences

Tools & technologies

Example employers

Check PointCyberArkPalo Alto NetworksSygniaDeloitteEYComsecMicrosoft

Job role

Security Engineerמהנדס אבטחת מידע

A Security Engineer designs, builds, and maintains the defenses that protect an organization's applications, infrastructure, and data. They implement security controls, harden systems, and build tooling that detects and prevents attacks across the technology stack.

Responsibilities

Design and implement security controls across applications and infrastructure
Harden cloud accounts, servers, and network configurations
Build and maintain detection, logging, and security automation tooling
Review architectures and code for security weaknesses
Manage identity, authentication, and secrets across systems
Respond to and help remediate security incidents and vulnerabilities

Required knowledge

Application and network security principles and the OWASP Top Ten
Cryptography fundamentals including encryption, hashing, and key management
Identity, authentication, and authorization models such as OAuth and RBAC
Cloud security and the shared responsibility model
Operating system and network internals as they relate to defense
Threat modeling, risk assessment, and secure design principles

Skills

Designing and implementing layered security defenses
Hardening systems, cloud accounts, and pipelines
Building security automation and detection tooling
Reviewing code and architecture for vulnerabilities
Managing secrets and identity securely at scale
Collaborating with engineers to embed security by design

Tools & technologies

AWS, Azure, and GCP security services
Terraform and Open Policy Agent
Wiz and Prisma Cloud
HashiCorp Vault
Python and Go
Burp Suite
Docker and Kubernetes
SIEM platforms such as Splunk and Sentinel
Okta

Example employers

WizCheck PointCyberArkPalo Alto NetworksMicrosoftGoogleSnykArmis

Job role

SOC Analystאנליסט מרכז תפעול אבטחה (SOC)

A SOC Analyst works in a Security Operations Center to continuously monitor an organization's systems, detect threats, and respond to security alerts in real time. They are the front line of defense, triaging events and escalating genuine incidents for response.

Responsibilities

Monitor security alerts and dashboards from SIEM and detection platforms
Triage and investigate alerts to separate real threats from false positives
Escalate confirmed incidents and follow response playbooks
Analyze logs, endpoint, and network telemetry for indicators of compromise
Document incidents, actions taken, and lessons learned
Tune detection rules and contribute to threat hunting efforts

Required knowledge

Network protocols and the TCP/IP stack as they relate to attacks
Common attack techniques and the MITRE ATT&CK framework
Operating system internals and log sources on Windows and Linux
Incident response lifecycle and escalation procedures
Cryptography and secure communication fundamentals
Threat intelligence concepts and indicators of compromise

Skills

Triaging high volumes of alerts efficiently and accurately
Investigating events across logs and telemetry sources
Following and improving incident response playbooks
Recognizing attack patterns and indicators of compromise
Communicating clearly under time pressure during incidents
Tuning detections to reduce alert fatigue

Tools & technologies

Example employers

Check PointCyberArkSygniaBank HapoalimDeloitteMicrosoftRadwareCymulate

Concentration

AI & Robotics בינה מלאכותית ורובוטיקה

Job roles a graduate of this concentration can step into:

Job role

ML / AI Engineerמהנדס למידת מכונה ובינה מלאכותית

An ML / AI Engineer designs, trains, and deploys machine learning models that power intelligent features in production systems. They turn data and research models into reliable, scalable services, spanning data preparation, model development, and integration with applications.

Responsibilities

Build and train machine learning and deep learning models for production use
Engineer features and prepare datasets for model training and evaluation
Evaluate models against business and statistical metrics and iterate
Deploy models as services and integrate them into application pipelines
Optimize model inference for latency, cost, and throughput
Build retrieval-augmented and LLM-based pipelines and prompts

Required knowledge

Linear algebra, probability, statistics, and multivariate calculus
Machine learning theory including supervised, unsupervised, and reinforcement learning
Neural network architectures and the backpropagation algorithm
Transformer architecture and the foundations of large language models
Model evaluation, bias-variance tradeoff, and generalization theory
Optimization methods such as gradient descent and regularization

Skills

Designing and training models for real-world problems
Feature engineering and data preprocessing at scale
Diagnosing model underfitting, overfitting, and data quality issues
Building and tuning LLM prompts and retrieval pipelines
Optimizing and serving models efficiently in production
Communicating model behavior and limitations to stakeholders

Tools & technologies

Example employers

NvidiaGoogleMicrosoftIntelMobileyeLightricksAmazonAI21 Labs

Job role

MLOps Engineerמהנדס MLOps

An MLOps Engineer builds and operates the infrastructure and automation that take machine learning models from experimentation to reliable production. They focus on reproducibility, continuous training, deployment, and monitoring of models at scale.

Responsibilities

Build automated pipelines for data ingestion, training, and deployment
Manage model versioning, experiment tracking, and a model registry
Deploy models as scalable services with CI/CD for machine learning
Monitor models in production for drift, degradation, and data quality
Provision and manage GPU and compute infrastructure for training
Automate retraining and rollback workflows for models

Required knowledge

Machine learning lifecycle and the foundations of model training
Distributed systems, scalability, and fault tolerance concepts
Containerization and orchestration theory
Continuous integration and delivery principles applied to ML
Data engineering concepts including pipelines and feature stores
Model monitoring concepts such as drift and observability

Skills

Designing reproducible and automated ML pipelines
Containerizing and orchestrating model training and serving
Implementing model monitoring and drift detection
Managing compute resources and cost for ML workloads
Automating deployment, rollback, and retraining
Collaborating with data scientists to productionize models

Tools & technologies

Example employers

NvidiaGoogleMicrosoftAmazon Web ServicesIntelMobileyeLightricksJFrog

Job role

Algorithm Engineerמהנדס אלגוריתמים

An Algorithm Engineer designs, implements, and optimizes the algorithms at the core of intelligent products, from machine learning and perception to search and optimization. They turn mathematical and research ideas into efficient, tested, production-ready code.

Responsibilities

Design and implement algorithms for perception, estimation, optimization, or learning
Translate research papers and mathematical models into efficient, tested code
Profile and optimize algorithms for speed, memory, and numerical stability
Benchmark algorithm variants and analyze accuracy, complexity, and trade-offs
Integrate algorithms into production systems and real-time pipelines
Collaborate with researchers and product engineers to refine requirements

Required knowledge

Algorithms, data structures, and complexity analysis
Linear algebra, probability, and optimization
Machine learning and statistical modeling foundations
Numerical methods and numerical stability
Signal or image processing fundamentals where relevant

Skills

Strong programming and software engineering
Mathematical modeling and problem decomposition
Performance profiling and optimization
Rigorous experimental design and benchmarking
Reading and reproducing research literature

Tools & technologies

Python: algorithm prototyping and development
C++: high-performance algorithm implementation
NumPy and SciPy: numerical computing
PyTorch: learning-based components
OpenCV: computer-vision algorithms
Numba or Cython: acceleration of hot loops
Git and CI: versioned, tested code
Profilers (perf, py-spy): performance analysis

Example employers

MobileyeIntelNVIDIAGoogleQualcommLightricksRafaelTrigo

Job role

Data Scientistמדען נתונים

A Data Scientist extracts insight from data using statistical analysis, machine learning, and visualization to inform decisions and build predictive models. They frame business problems quantitatively, analyze data rigorously, and communicate findings to stakeholders.

Responsibilities

Frame business questions as data and modeling problems
Explore, clean, and analyze datasets to uncover patterns and insights
Build and evaluate statistical and machine learning models
Design and analyze experiments such as A/B tests
Create visualizations and dashboards to communicate findings
Present results and recommendations to business stakeholders

Required knowledge

Probability, statistics, and statistical inference
Machine learning theory including supervised and unsupervised methods
Experimental design and hypothesis testing
Linear algebra and optimization fundamentals
Data wrangling, feature engineering, and exploratory analysis concepts
Causal inference and bias-variance tradeoff

Skills

Translating ambiguous business problems into analyses
Cleaning and exploring messy real-world datasets
Building and validating predictive models
Designing and interpreting controlled experiments
Communicating insights through visualization and storytelling
Writing reproducible analysis code

Tools & technologies

Example employers

GoogleMicrosoftMetaWixMonday.comTaboolaRiskifiedPlaytika

Job role

NLP Engineerמהנדס עיבוד שפה טבעית

An NLP Engineer builds systems that understand, generate, and process human language using machine learning and large language models. They develop pipelines for tasks such as classification, extraction, search, and conversational AI, and deploy them into production.

Responsibilities

Build and fine-tune models for text classification, extraction, and generation
Develop retrieval-augmented generation and LLM-based pipelines
Preprocess and tokenize text data and build training datasets
Evaluate language models against task-specific and human metrics
Optimize inference for latency, cost, and quality in production
Design prompts, guardrails, and evaluation harnesses for LLM applications

Required knowledge

Linear algebra, probability, and statistics
Machine learning and deep learning theory
Transformer architecture and the foundations of large language models
Natural language processing concepts such as tokenization and embeddings
Information retrieval and vector search fundamentals
Model evaluation, generalization, and bias considerations

Skills

Building and fine-tuning language models for real tasks
Designing retrieval and prompting pipelines for LLMs
Preprocessing and curating text datasets
Evaluating NLP systems with appropriate metrics
Optimizing and serving language models efficiently
Diagnosing model failures and hallucinations

Tools & technologies

Python
PyTorch
Hugging Face Transformers and Tokenizers
spaCy and NLTK
LangChain and LlamaIndex
FAISS and Pinecone
OpenAI and Anthropic APIs
Weights and Biases
Docker

Example employers

AI21 LabsGoogleMicrosoftAmazonLightricksVerbitGongMeta

Job role

Computer Vision Engineerמהנדס ראייה ממוחשבת