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Requirements:
* Excellent interpersonal skills, our center is first and foremost a service oriented unit
* High motivation for research, learning, and attention to detail
* Ability to learn quickly, professionalism, and initiative
* High level verbal and written communication skills in Hebrew and English- required
* Excellent ability to manage and prioritize tasks while working across multiple interfaces
* Strong commercial orientation, with understanding and familiarity with the worlds of finance, economics, capital markets, and regulation- an advantage
* Preference for candidates with a Bachelors degree in Business Administration, Economics, Marketing, Accounting, or Law
An equal opportunity employer. We are committed to diversity and inclusion and believe they are a source of strength, growth, and continuous learning. We foster an inclusive environment and empower women and men alike.

Requirements:
Hands-on experience building production workflows using automation platforms such as Zapier, Make, n8n, Workato, or similar
Practical experience applying AI and LLM tools to real operational workflows - including OpenAI, Anthropic, Google Gemini, or open-source models - with at least one deployed example you can speak to concretely
Logical approach, thinking in structured steps and knowing how to break down workflows, sequence them correctly, and designing how they should run before building them.
Comfort working across both technical and non-technical stakeholders and translating between the two
Prioritizing building and shipping over prolonged planning; moving from idea to production quickly.
Driving initiatives forward with minimal oversight; proactively engaging the right stakeholders without being directed to. Taking ownership and leading confidently.
Experience in teaching and change management; treating adoption as part of the job, not an afterthought. Demonstrated patience with others.
2-5 years of relevant experience in workflow automation, AI operations, RevOps, or a technical GTM or systems role
Some nice-to-haves:
Experience with APIs, data pipelines, or low-code / no-code platforms
Exposure to CRM, support, or operational SaaS systems
Background in operations, systems design, or process improvement

Requirements:
4+ years of experience in People Operations, HR Operations, project management, business operations, or a similar role.
Exceptional organization and follow-through - you naturally keep track of details, owners, deadlines, and next steps.
Strong project management instincts and the ability to move multiple initiatives forward at the same time.
High ownership. When something is unclear or stuck, your instinct is to create clarity and push it forward.
A pleasent emphatetic mindset, and a strong service oreitnation, with no ego.
Comfort working with systems, processes, data, and documentation.
Experience with HRIS platforms and strong Excel or Google Sheets skills.
Comfortable and curious using AI, automations, and better ways of working.
Full professional fluency in Hebrew and English.
Strong judgment, common sense, and the ability to operate effectively in a fast-moving environment.
Nice to have
Experience working in a global or fast-growing technology company.
Experience with an HRIS such as bamboo or a similar platform.
Experience supporting performance, compensation, talent, or organizational processes.
Hands-on experience with project management, automation, or reporting tools.

Requirements:
6-8+ years of hands-on experience in senior software engineering positions.
Hands-on experience building and shipping agentic workflows or LLM-powered systems in production, not just prototypes.
Real experience working across agent harnesses (e.g., Claude Code and similar), and hands-on understanding of agent context: how it's built, scaffolded, and kept effective at scale.
Practical understanding of the actual building blocks: LLMs, RAG, tool use, evaluations, and human-in-the-loop patterns, not just theoretical familiarity.
Strong software engineering fundamentals: you can design, build, and operate a system end to end.
A demonstrated ability to work without a pre-defined spec: given a goal or a KPI, you can find the problem, scope the solution, and build it.
Product judgment: you can separate what's worth building from what isn't, and you know how to tell whether it actually worked.
Strong discovery skills: you can sit with engineers, map how work actually happens today, and identify where automation genuinely helps versus where it doesn't.
Strong communication skills: you can translate between technical tradeoffs and the people who need to understand the impact.
Advantages
A cost-aware mindset: you treat tokens like a resource to be managed, not an afterthought.
Experience building on top of Kubernetes, containers, or CI/CD infrastructure in production.
Experience with MCP-based tooling, agent orchestration frameworks, or LLM gateways.
Familiarity with observability tooling (e.g., Datadog) for monitoring agent or platform health.
Background in a fast-paced, high-growth B2B SaaS environment.
Exposure to health tech, healthcare institutions, or behavioral health.

Requirements:
4+ years of experience leading a team of at least 5 developers, building and maintaining SaaS applications at scale in production
5+ years of software engineering experience working on production applications with real-world users
Experience building E2E Web Services working with big amounts of data.
Proficient in React/Angular/Other modern JS framework and a JavaScript tech stack background
Experience with Python and microservices.
Experience working with AWS.
Working with LLMs - LiteLLM, Langfuse, LangGraph.

Requirements:
At least 5 years of experience with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.
Hands-on experience working on ML/AI-powered products in production, with strong understanding of requirements for integrating data platforms with AI features.
Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, and experience supporting their deployment or integration.
Familiar with or have worked with these technologies (or alternatives):
Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
API Development: FastAPI, micro-service architecture, SFTP
Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
ML/AI: ML/LLM libraries and frameworks (such as Gemini, Hugging Face, etc.)
Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
Demonstrated ability to optimize performance and ensure high availability, scalability, and reliability of backend/data systems.
Strong foundation in best practices for data quality, governance, security, and observability.
Ability to collaborate effectively with engineering, data science, and product teams in a cross-functional setting.
Track record of innovative thinking on feature-level implementations, metric definitions, and AI/data integrations.
Service-oriented approach, particularly in high-responsibility, on-call situations.

Requirements:
7+ years of hands-on experience building, deploying, and operating large-scale, production cloud systems end-to-end.
Strong Computer Science foundations: Solid grasp of software design principles, concurrency, data structures, and cost/performance trade-offs.
Cloud-Native & Event-Driven Systems: Hands-on experience designing and operating cloud-native, event-driven architectures and working with modern databases (SQL, NoSQL, or vector DBs).
Language Proficiency: Deep proficiency in **Python** (or equivalent backend languages).
Cross-Domain Adaptability: Comfortable working across backend contexts, including data pipelines, backend core logic, and applicative microservices.
Ownership Mindset: A strong sense of personal accountability and a proven track record of taking complex backend systems from zero to production.
Education BSc in Computer Science, Software Engineering, or equivalent practical experience.
Advantages :
AI Agent Workflows Experience building or integrating AI agents, LLM orchestration, or modern AI frameworks into production services.
DevOps & CI/CD: Hands-on experience setting up robust, automated CI/CD pipelines and infrastructure-as-code.
Full Stack Flexibility: Prior exposure to modern Frontend/UI frameworks (e.g., React, TypeScript)

Requirements:
7+ years of experience in cybersecurity, with a strong focus on incident response
Proven experience managing complex, high-severity cyber incidents
Deep understanding of threat actors, attack techniques, and forensic methodologies
Experience leading global or distributed teams in a follow-the-sun model
Strong communication skills in English
Relevant certifications (e.g., GCFA, GCIH, CISSP, or similar) preferred.