לוח משרות דרושים הייטק תוכנה עבודה היברידית

Requirements:
What we need to see:

B.SC./M.SC. or equivalent experience in Electrical Engineering/Communication Engineering/Computer Engineering.

5+ years of validated experience in RTL Frontend ASIC Verification (Chip Design).

High Level of English.

Ways to stand out from the crowd:

Experience in RTL Frontend ASIC Verification.

Knowledge in Specman.

Knowledge in Verilog.

Requirements:
- 4+ years proven experience leading large scale technology projects, involving platform architecture, databases, and AI/ML
- Strong understanding of SDLC, agile delivery, technical architecture, data and cloud
- Ability to translate complex technical concepts into actionable project plans
- Exceptional communicator and problem solver
- Bachelors degree in Industrial Engineering, Computer Science, or related field
- PMP, Scrum Master, or Agile certifications
- Knowledge of search, AI, LLM, ML - an advantage
- Background in product management - an advantage
- Experience leading international, distributed teams
- High proficiency in English

Requirements:
Experience:
A minimum of 4 years of experience as a Software Developer and at least 2 years of experience in team management.
Proven experience in leading end-to-end (E2E) development projects from concept to delivery.
Strong track record of architecting and developing large-scale, high-performance products or services.
Technical Expertise:
Proficiency with Node.js and web frameworks.
Strong experience with front-end frameworks such as React, Angular 2, or Vue.js.
Familiarity with React Native, iOS, or Android development is a plus.
Ability to translate complex business requirements into scalable architecture and deliver high-quality, maintainable code.
Exceptional problem-solving skills with a focus on simplifying complex challenges and delivering solutions efficiently.
Educational Background:
BS/MS/Ph.D. in Computer Science, a related field, or equivalent practical experience.

Requirements:
1. Technical Expertise
Cloud Data Platforms: Expertise in Google Cloud Platform (GCP)
services, especially in data-related services like BigQuery, Cloud SQL,
Dataproc, Pub/Sub, and Dataflow.
Data Engineering: Strong knowledge of data pipelines, ETL/ELT
processes, and data integration using GCP tools.
Database Management: Experience with both relational and
non-relational databases, including MySQL, PostgreSQL, and NoSQL
solutions like Firestore or Bigtable.
Programming Skills: Proficiency in Python, SQL, and possibly other
languages like Java or Scala, with a focus on data manipulation and
processing.
APIs and Integrations: Experience working with Google APIs and
third-party APIs for data extraction and integration.
Machine Learning: Familiarity with Google Cloud AI tools, such as
Vertex AI, and how to integrate machine learning workflows into the data
architecture.
Data Governance: Knowledge of data security, privacy, governance, and
regulatory requirements (GDPR, HIPAA, etc.).
2. Leadership and Management
Team Management: Ability to lead a team of data engineers, analysts,
and architects, providing guidance, mentorship, and performance
management.
Project Management: Strong skills in managing data projects, ensuring
timely delivery while meeting client requirements.
Collaboration: Experience working cross-functionally with stakeholders
such as solution architects, developers, and business teams to translate
business needs into data solutions.
Resource Allocation: Efficiently managing cloud resources to optimize
cost and performance.
3. Client-Facing Skills
Consulting: Experience in providing consulting services to clients,
including understanding their data needs, providing solutions, and
guiding them through the data modernization process.
Pre-sales Support: Supporting sales teams in scoping out client
projects, preparing presentations, and explaining technical aspects of
data solutions during pre-sales.
Client Relationship Management: Building and maintaining strong
relationships with clients to ensure satisfaction and long-term
partnership.
4. Certifications and Education
● Google Cloud Certifications:
● Professional Data Engineer (preferred)
● Professional Cloud Architect (preferred)
● Other Certifications: Optional certifications in data engineering or
machine learning from organizations like Cloudera, AWS, or Microsoft
Azure can be advantageous.
● Educational Background: Bachelors or Masters degree in Computer
Science, Data Science, Engineering, or a related field.
5. Soft Skills
● Problem-Solving: Ability to troubleshoot data-related issues and
implement scalable solutions.
● Adaptability: Ability to keep up with the rapidly changing cloud and data
landscape.
● Communication: Excellent verbal and written communication skills to
explain complex data systems to non-technical stakeholders.

Requirements:
Excellent phone and cold calling skills.
Excellent verbal and written communications skills (English & Hebrew)
Ability to multitask, prioritize, and manage time efficiently.
Proficiency in CRM is an advantage.
Previous experience in an outbound sales call center or a related sales position.
Technical background.
Ability to achieve targets.
BA/BS degree or equivalent.

Requirements:
A passionate, positive leader who thrives in complex, fast-moving environments
Strong communication and storytelling skills with the ability to influence across technical and non-technical stakeholders
8+ years of experience in product management, with at least 5 years managing PMs and leading product lines
Proven success in delivering B2B SaaS or hybrid software products in data security, privacy, governance, or compliance domains
Experience building or scaling data classification productswhether content-based, metadata-based, AI-enhanced (ML/NLP/LLM), or policy-driven
Familiarity with privacy frameworks and regulations such as GDPR, CCPA, HIPAA, and frameworks like NIST or ISO 27701
Experience working with cloud infrastructure providers (AWS, Azure, GCP) and data systems (e.g., cloud storage, SaaS apps, databases)
Demonstrated ability to synthesize customer pain points into actionable roadmaps and drive cross-functional execution
Deep curiosity and empathy for customers; always looking for ways to solve real problems
Strong technical background (e.g., engineering or technical PM experience) is a plus

Requirements:
At least 3 years of experience in infrastructure development.
Experience working in Cloud environments (concepts, methodologies, CI/CD), preferably in large-scale or distributed systems.
Experience leading automation projects from scratch (design, integration with external interfaces, testing, and implementation).
Strong in Object-Oriented Programming, MVC, Design patterns, and SOLID principles.
Familiarity with relational and non-relational databases and SQL.
Experience with web services development (SOAP, REST).
Excellent communication and collaboration skills, with the ability to influence technical and non-technical stakeholders.
Bachelor's degree in computer science, Software Engineering, or related field.
Familiarity with container technology (Docker & AKS) an advantage.
Experience with API design, development, and integration patterns an advantage.

Requirements:
6 years of experience in building complex backend systems.
Experience in C# / JAVA / .NET
Expertise in microservice architecture
Proficiency in working with various backend technologies such as databases, caches, k8s, containers, Kafka and cloud environments.
Excellent problem-solving skills and ability to work well in a team.
Experience in the cybersecurity space is an advantage.

Requirements:
5+ years of Product Management experience.
Genuine passion for AI, Cybersecurity and the space where they intersect a must
Bachelors degree in Computer Science, Engineering, or relevant technical experience.
Proven success launching LLM-powered cybersecurity products.
Strong understanding of LLM use cases and technologies (e.g., AI agents and frameworks, copilots, MCP, A2A).
Experience in cybersecurity domains (e.g., threat detection, DLP, identity, or cloud security) strongly preferred.
Familiarity with AI security risks (e.g., prompt injection, jailbreaking, data leakage, model abuse, sensitive data governance).
Ability to engage with technical concepts (APIs, data pipelines, LLM architectures, security controls) and translate them into customer value.
High proficiency in English (spoken and written).
Exceptional communication and collaboration skills to work with both technical and business teams.
Customer-focused mindset with a drive to deliver impactful solutions.
Comfortable operating in a rapidly evolving market with shifting technologies and threats.