לוח משרות דרושים, לחיפוש זה נמצאו 35,110 משרות

Requirements:
Experience: At least 2 years of experience managing paid campaigns and/or organic social media channels. Copywriting Skills: Excellent communication and writing skills in Hebrew, with a very high level of English and the ability to create sharp, engaging, and non-generic marketing content. Video Editing: Experience editing videos for Reels/Stories is a significant advantage. People Skills & Energy: The ability to engage people, motivate them, and guide them. Technological Literacy: Curiosity and a basic understanding of the software, cyber, or cloud world, or the ability to learn quickly. Business-Oriented: A business mindset and an understanding that every marketing activity should contribute to results, not just "look good." Must Have: Experience working with AI tools.
This is a 50% part-time position.

Requirements:
Strong technical background - Must. Engineering, security research, or equivalent hands-on technical role. You can read a stack trace, reason about request flow through a service, and have a point of view on why existing AppSec categories under-deliver.
Security research background - Must. Application security, vulnerability research, offensive security, or a technical military intelligence role. Comfortable going deep on CVE classes, exploitation patterns, and runtime signals.
Product experience. Formal PM, founding engineer with product instincts, or a tech lead who shaped what shipped. We care about evidence you delivered things customers actually used - not the title on your last business card.
AI-native operator. You've built something with modern AI tooling - an agent, an eval harness, a workflow - not just used it.
Hands-on by default. Comfortable in fast-paced startup environments where there's no one to hand the work off to.
Clear writer in English. Slack messages, specs, customer notes. Compression matters.

Requirements:
Core Security & Operations
3+ years experience in SecOps / Cloud Security / Security Engineering
Hands-on experience securing Google Cloud Platform environments
Strong understanding of:
IAM (roles, service accounts, workload identity)
Network security (VPCs, firewall rules, load balancers)
Organization policies and security baselines
Experience operating and tuning security controls in production

Detection, Monitoring & Response
Experience with Google Cloud Security Command Center
Experience with Google SecOps (Chronicle) or equivalent SIEM
Building and tuning:
Detection rules
Alerts
Dashboards
Incident triage, investigation, and response in cloud environments
Log ingestion and normalization from cloud and third-party sources

Automation & Engineering
Strong scripting skills (Python preferred)
Security automation (SOAR-like workflows, custom tooling)
Experience integrating security tooling via APIs
CI/CD security controls (shift-left, pipeline security checks)
Cloud & Platform Security

Experience securing:
GKE
Cloud Run
Compute Engine
Knowledge of container security concepts (images, registries, runtime)
Vulnerability management and remediation workflows

Governance & Compliance
Experience with security posture management
Familiarity with common frameworks (ISO 27001, SOC 2, CIS Benchmarks)
Risk assessment and security findings remediation

Nice to Have:
Experience with Wiz, Prisma Cloud, or similar CSPM tools
Experience with threat modeling and attack simulations
Experience working with regulated environments
Google Cloud security certifications

Requirements:
Proven experience as a Cloud Architect, Cloud Solutions Architect, or in a similar cloud infrastructure role.
Deep understanding of cloud computing principles, microservices architectures, and serverless computing.
Expertise in at least one major cloud provider (GCP, AWS, Azure) and their core services (compute, storage, networking, databases).
Strong knowledge of containerization platforms and orchestration tools (Docker, Kubernetes).
Extensive experience with Infrastructure as Code tools (e.g., Terraform, CloudFormation, Pulumi) and scripting languages (Python, Bash).
Solid understanding of cloud networking (VPC, VPN, routing, load balancing) and cloud security concepts.
Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
Strong problem-solving, analytical skills, and a customer-centric mindset.
Bachelors degree in Computer Science, Engineering, or a related field.
Advantage: Professional-level cloud certifications (e.g., Google Cloud Professional Cloud Architect, AWS Certified Solutions Architect - Professional).

Requirements:
You've shipped agentic systems to production - real orchestration, tool use, structured outputs, and the failure modes that only appear at scale. Not "I've called an LLM API."
You've built the evaluation discipline, not just consumed it: trajectory tests, golden datasets, regression gates, offline replay. "It seems better" is not a metric, and you have opinions about what is.
Deep backend and distributed-systems engineering. Strong Python, and comfort with workflow orchestration (Temporal or equivalent), streaming, and cloud-native infrastructure. Agent platforms are systems problems wearing an AI hat.
Fluency across the modern agent stack - LangChain/LangGraph-style frameworks, multi-provider routing, structured output contracts, prompt and context engineering - with the judgment to know which parts are load-bearing and which are fashion.
Security literacy. Enough to reason about whether an agent's security output can be trusted, and to argue with researchers on the merits. You don't need to be a vulnerability researcher.
Influence without authority. You'll change how three teams work with no one reporting to you. Show us where you've done that.
Advantage: experience with AI/LLM security - red-teaming agents, prompt injection, or agentic attack patterns.
Advantage: background in cybersecurity, detection engineering, or WAF/mitigation systems.
Advantage: you've driven AI adoption across a whole company, not only an engineering org.

Requirements:
Requirements & Qualifications:

Leadership Experience: 2+ years of experience leading technical teams (architects, DevOps, or engineering squads), including mentoring, task prioritization, and delivery accountability - ideally in a professional services or consulting environment.

Communication & Presentation: Outstanding verbal and written communication skills in English & Hebrew. Proven ability to conduct discovery calls and articulate sophisticated technical concepts to both engineering teams and non-technical business executives, and to represent the company at a senior level.

Cloud Platform Expertise: 5+ years of proven experience architecting, deploying, and managing complex production workloads on Google Cloud Platform (GCP) and/or Amazon Web Services (AWS), with deep knowledge of their core services (compute, storage, networking, databases).

Core Technical Foundations: Strong foundational knowledge of operating systems (Linux/Windows), virtualization environments, database architectures (SQL/NoSQL), and proficiency in scripting languages (such as Python and Bash) for automation and troubleshooting.

Modernization & Serverless Mastery: Practical experience implementing containerized solutions (Docker, Kubernetes/GKE/EKS) and serverless technologies (Cloud Run, AWS Fargate, ECS, Lambda, Cloud Run Functions).

Hands-On DevOps & IaC: Strong, hands-on background in DevOps practices. Expert-level knowledge of Infrastructure as Code (IaC) tools - specifically Terraform - along with deep experience in CI/CD pipeline construction.

Migration Experience: Proven track record of guiding enterprise migrations (re-hosting, re-platforming, and refactoring), particularly On-Prem to Cloud or cloud-to-cloud migrations (such as AWS to GCP).

Client-Facing Professionalism: A consultative, customer-centric mindset with strong analytical, scoping, and problem-solving abilities, and the maturity to own decisions independently under broad executive guidance.

AI/ML Familiarity: An understanding of the modern AI landscape, with the ability to identify opportunities where Generative AI can drive value for clients.

Education: Bachelor degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).

Preferred Advantages
Multi-Cloud experience: Hands-on architectural and deployment experience with both GCP and AWS.
Prior experience as a Team Leader, Delivery Lead, or Principal Architect in a cloud consulting / MSP / professional services company.
One of the following Professional-level cloud certifications:
- Google Cloud Professional Cloud Architect
- AWS Certified Solutions Architect - Professional
Deep expertise in FinOps methodologies and cloud cost allocation tools.

Requirements:
Deep, hands-on WAF expertise across multiple major providers - you've written, tuned, and operated real rules in production on several of: AWS WAFv2, Cloudflare, F5, Imperva, Akamai, Azure, GCP, Fortinet, ModSecurity/CRS. Not "managed a WAF vendor relationship" - written the rules.
You know the caveats cold. Body-inspection limits and oversize handling, text transformations and normalization order, encoding and unicode evasion, parameter pollution, chunked and multipart edge cases, rule precedence and evaluation order, WCU/capacity economics, and how each provider's expression language quietly differs from the others.
Strong security research background - application security, vulnerability research, or offensive security. You can read an advisory, build the PoC, derive the variants nobody published, and explain exactly which request component carries the exploit primitive.
A real feel for the false-positive tradeoff. You've had to defend a blocking decision to someone whose production traffic you broke, and you know why "block everything suspicious" is not a security posture.
Comfortable in code. Enough Python (or similar) to automate replay, build variant generators, and query exploit and traffic data yourself rather than waiting on someone.
Fast under pressure, systematic afterward. You can get a solid rule out the door when a customer needs one today - and your instinct once it ships is to build the check that catches the whole class, not just the instance you fixed.
Advantage: virtual patching / vulnerability-mitigation experience, or time on a WAF vendor's rules or research team.
Advantage: hands-on with LLMs and agentic tooling - you'll be shaping an AI system's output, and it helps to understand how it fails.