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Requirements:
5+ years of backend development experience, ideally building scalable and distributed systems.
Deep expertise in Python and modern cloud-native architectures.
Proven experience with AI-enhanced systems - integrating or working with LLMs, RAG, or machine learning pipelines.
Understanding of data-intensive architectures, including streaming, caching, and dataflow optimization.
Strong collaboration and communication skills, with the ability to translate AI concepts into production-grade systems.
Advantage: Familiarity with vector databases, prompt engineering, and evaluation frameworks for AI models.
Advantage: Background in cybersecurity, runtime analysis, or agentic AI design patterns.

Requirements:
Core Data Engineering
3+ years of experience as a Data Engineer
Strong hands-on experience with Google Cloud Platform
Advanced SQL (BigQuery performance, partitioning, clustering)
Strong Python (data pipelines, APIs, batch & streaming jobs)
Experience building batch and streaming pipelines
BigQuery
Dataflow / Apache Beam
Pub/Sub
Cloud Storage
Data modeling for analytics and ML use cases
Production troubleshooting, optimization, and cost awareness

ML & GenAI
Experience supporting ML pipelines (training, inference, feature prep)
Hands-on with at least one of:
Vertex AI
Feature stores
Model inference pipelines
Experience working with LLM-based systems, including:
Embeddings generation
Vector databases / similarity search
RAG-style pipelines
Ability to prepare, version, and serve data for GenAI / ML workloads

Platform & Engineering
Experience with Airflow / Cloud Composer or equivalent orchestration
CI/CD pipelines for data & ML workloads
Infrastructure-as-code familiarity (Terraform preferred)
Understanding of IAM, data security, and access controls on GCP

Nice to Have
Experience with FinOps / cost optimization
Experience with real-time ML or low-latency inference
Experience with monitoring & observability for data/ML pipelines
Google Cloud certifications (Data Engineer / Architect)

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).