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Requirements:
* 3+ years of hands-on Python development with a strong understanding of best practices and software design principles
* Experience with a Python web framework - Django, Flask or FastAPI
* Strong fundamentals with the ability to read, debug, and pick up unfamiliar languages and codebases independently
* Comfortable working in Linux environments, including shell scripting, system operations, and troubleshooting
* Strong analytical, problem-solving, and organizational skills
* Clear communication and collaboration skills - this role works closely with non-technical stakeholders
* Hands-on experience with AI-assisted development tools (Claude Code, Copilot, Cursor, or similar) Preferred Qualifications
* Experience with Go, or a strong interest in picking it up
* Hands-on familiarity with Kubernetes - deployments, services, and troubleshooting (EKS experience a plus)
* Familiarity with frontend development frameworks, specifically NextJS or other React based frameworks
* Cloud environment experience, with AWS being a strong advantage
* Knowledge of system-level topics such as storage and networking
About Infinidat Infinidat’s enterprise storage portfolio provides global Fortune 500 enterprises and service providers with best-in-class solutions for primary storage, next-generation data protection, disaster recovery, business continuity, and cyber resilience. Infinidat’s acclaimed InfuzeOS is the one of the most flexible and complete enterprise software-defined storage architectures in the industry. We recently announced powerful enhancements, an extensive expansion, and the dynamic evolution of our award-winning G4 enterprise cyber and AI storage solutions! Not only did Infinidat win over 40 awards in 2025 , but was named a Gartner® Peer Insights™ Voice of the Customer Award for Primary Storage for the 7th time!

Requirements:
* 7+ years of experience as a Python developer. Strong backend proficiency in Python or equivalent (Go, Java)
* Solid database experience, particularly with PostgreSQL (query design, optimization, schema modeling)
* Hands-on experience designing and building microservices
* Familiarity with Docker and Kubernetes for containerization and orchestration
* Experience with message brokers (e.g., RabbitMQ, Kafka) - Preferred Qualifications
* Experience leveraging AI-assisted development tools such as Cursor or GitHub Copilot
* ClickHouse experience — a big plus for our data-heavy workloads
* Familiarity with Go (Golang) — a plus - JavaScript proficiency — a plus
* Experience working with cloud platforms, especially AWS — a plus
?About Infinidat Infinidat’s enterprise storage portfolio provides global Fortune 500 enterprises and service providers with best-in-class solutions for primary storage, next-generation data protection, disaster recovery, business continuity, and cyber resilience. Infinidat’s acclaimed InfuzeOS is the one of the most flexible and complete enterprise software-defined storage architectures in the industry. We recently announced powerful enhancements, an extensive expansion, and the dynamic evolution of our award-winning G4 enterprise cyber and AI storage solutions! Not only did Infinidat win over 40 awards in 2025 , but was named a Gartner® Peer Insights™ Voice of the Customer Award for Primary Storage for the 7th time!

Requirements:
* Minimum of 2-3 years of Hands-on experience in complex hardware debugging across a wide range of Platforms, including enterprise servers, BMC, PCIe, IPMI, SAS/SATA/NVMe SSDs, JBODs, Ethernet cards, PDUs, UPSs, and other related components
* Bachelor’s degree in Electrical Engineering, Computer Engineering, or an equivalent field -MUST
* Experience in scripting and automation using Bash and Python- MUST!
* Experience with Linux-based environments, system-level tools, logs, kernel interfaces, drivers, and debugging workflows
* Solid understanding of electrical engineering and computer networking concepts
* Hands-on problem solver with a demonstrated “ownership” mindset, able to operate effectively both independently and within cross-functional teams.
* Experience working with large-scale complex hardware enterprise products.
* Highly organized with strong attention to detail, can prioritize and manage multiple tasks in a fast and dynamic environment
* Excellent verbal and written English communication skills
About Infinidat Infinidat’s enterprise storage portfolio provides global Fortune 500 enterprises and service providers with best-in-class solutions for primary storage, next-generation data protection, disaster recovery, business continuity, and cyber resilience. Infinidat’s acclaimed InfuzeOS is the one of the most flexible and complete enterprise software-defined storage architectures in the industry. We recently announced powerful enhancements, an extensive expansion, and the dynamic evolution of our award-winning G4 enterprise cyber and AI storage solutions! Not only did Infinidat win over 40 awards in 2025 , but was named a Gartner® Peer Insights™ Voice of the Customer Award for Primary Storage for the 7th time!

Requirements:
2+ years of hands-on experience in application penetration testing.
Strong understanding of OWASP Top 10 and CWE Top 25, with proven experience identifying vulnerabilities and supporting practical remediation strategies.
Familiarity with high-level programming languages (Java, JS, Python, etc.).
Relevant App PT training and certifications such as EWPTX, OSWE, etc.
Strong English communication skills, with the ability to communicate technical topics clearly in client-facing discussions.
Advantage: Deep understanding of the LLM Top 10, AI security risks, MCP security risks, and AI/LLM hacking techniques.
Advantage: Proven experience in secure code review or high-level code auditing.
Advantage: Knowledge of Secure SDLC practices, and methodologies, including Microsoft SDL, OWASP SAMM, and OWASP ASVS.

Requirements:
Professional Experience: 3+ years of experience in dedicated AI development (LLMs, agentic workflows, RAG).
Senior Engineering Track: Alternatively, we value 7+ years of Senior Software Engineering experience combined with at least 1 year of deep AI development.
Education: A Bachelors or Masters degree in Computer Science or Electrical Engineering is a major bonus.
Technical Mastery: Deep proficiency in Python and the modern AI stack, with the ability to architect systems that require high reliability.

Requirements:
10+ years in enterprise cybersecurity sales, with 5+ in a leadership role carrying global/regional numbers.
Startup experience - including as a first or early sales leader who built a motion from (close to) zero, not only inherited one.
Demonstrated ownership of a business line, region, or P&L, with a track record of consistently exceeding targets.
Deep domain knowledge across several of: AI security, API security, AI agent security, Physical AI, XDR, and cloud security.
Experience selling into large enterprises with long, complex sales cycles across various verticals including financial services, healthcare, telecom, technology, energy, and industrial.
Proven success selling complex opportunities utilizing MEDDPICC and other sales methodologies, high-ARR solutions to large global enterprises.
Proven experience in multi-stakeholder deals involving CISOs, security architecture, business owners, procurement, and legal.
Strong technical depth - able to run pre-sales conversations independently: architecture, integration, POV scoping, and security review.
Genuinely hands-on - comfortable building the pipeline, the deck, and the business case yourself.
Advantage: Familiarity with emerging AI security frameworks and standards (OWASP Top 10 for API, MCP, LLM, MITRE, NIST AI RMF, EU AI Act, CRA, and more).
Experience working with partner and channel motions alongside direct sales.
Prior experience as a solutions engineer or in a technical role earlier in your career.
Fluent English; based in Israel, working from our Herzliya HQ.
Global mindset with willingness to travel extensively (est. 40-50%).

Requirements:
4+ years of experience building machine learning and deep learning solutions end-to-end, from research and experimentation through production.
MSc or PhD in Computer Science, Mathematics, Engineering, Statistic, or a related field, with strong foundations in machine learning, optimization, and statistical modeling.
Experience building machine learning solutions for real-time bidding (RTB), programmatic advertising, pricing, or other large-scale optimization problems.
Strong software engineering skills in Python or Java, with experience developing production ML systems.
Proven ability to take machine learning models from prototype to scalable, high-performance production environments.
Bonus points if you have:
Experience building machine learning models for bid optimization, auction systems, pricing, or large-scale recommendation systems.
Experience using AI coding tools (such as Claude Code or Cursor) to accelerate development, experimentation, and code quality.

Requirements:
Advanced academic training (MSc/PhD) with strong grounding in applied mathematics, optimization, control theory, or a related quantitative field
Strong Algorithmic Problem-Solving Experience (6+ years), and 2+ years of Managerial or Technical Leadership Experience
Production-Grade Algorithm Engineering Experience
Experience Driving Measurable Business Impact Through Algorithmic Improvements
Experience interfacing effectively with engineering teams to deliver complex algorithms into production
Experience leveraging agent-based coding tools to accelerate development, experimentation, and code quality
Bonus points if you have:
Experience with Real-Time Bidding, Auction Theory

Requirements:
Advanced academic training (MSc/PhD) with strong grounding in applied mathematics, optimization, control theory, or a related quantitative field
Strong Algorithmic Problem-Solving Experience (6+ years), and 2+ years of Managerial or Technical Leadership Experience
Production-Grade Algorithm Engineering Experience
Experience Driving Measurable Business Impact Through Algorithmic Improvements
Experience interfacing effectively with engineering teams to deliver complex algorithms into production
Experience leveraging agent-based coding tools to accelerate development, experimentation, and code quality
Bonus points if you have:
Experience with Real-Time Bidding, Auction Theory

Requirements:
Currently pursuing a B.Sc. in Computer Science, Software Engineering or a related technical field
Strong programming fundamentals and hands-on experience with at least one language such as Java, JavaScript or Python
Comfortable working in a Linux environment and using git
Basic understanding of software builds, automated testing and CI/CD, with familiarity with tools such as Jenkins, Artifactory, Bitbucket/GitHub, Bazel, Gradle or Maven
Familiarity with Docker, Kubernetes, Helm or infrastructure/configuration automation
Ability to troubleshoot technical issues and automate repetitive work
Experience using AI coding agents at scale for development work, with exercising judgment, providing clear context and acceptance criteria, verify their output, protect sensitive data and own the final contributions.
Basic familiarity with LLM APIs, agent skills, plugins or tools integrations, plus an understanding of how context limits and token usage affect quality, latency and cost
Passion for simplifying developer workflows, automating repetitive processes and solving challenging infrastructure problems at scale
Bonus points if you have:
Experience building or maintaining shared CI/CD pipelines used by many developers, services or teams
Hands-on work with production infrastructure, release engineering, DevOps or developer tooling in a company, technology unit or active open-source project

Requirements:
4+ years of experience building machine learning and deep learning solutions end-to-end, from research and experimentation through production.
MSc or PhD in Computer Science, Mathematics, Engineering, Statistics, or a related field, with strong foundations in machine learning, optimization, and statistical modeling.
Experience building machine learning solutions for real-time bidding (RTB), programmatic advertising, pricing, or other large-scale optimization problems.
Strong software engineering skills in Python or Java, with experience developing production ML systems.
Proven ability to take machine learning models from prototype to scalable, high-performance production environments.
Bonus points if you have:
Experience building machine learning models for bid optimization, auction systems, pricing, or large-scale recommendation systems.
Experience using AI coding tools (such as Claude Code or Cursor) to accelerate development, experimentation, and code quality.

Requirements:
3+ years experience in leading and managing software development teams.
Experience developing large scale distributed systems and solid understanding of production system infrastructure
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures, and concurrent/multi-threaded programming
5+ years programming experience in Java or equivalent Object-Oriented language
Experience with SQL and No-SQL
Highly Proficient in Linux environment
Demonstrated ability to collaborate effectively across multiple teams and drive alignment.
B.Sc in computer science or equivalent experience
Bonus points if you have:
Experience in Big Data tools
Knowledge in algorithms, data-mining and machine learning

Requirements:
2+ years of experience in a company operating in the agentic AI / AI infrastructure space, having owned and developed an AI product in production at scale.
10+ years leading high-scale R&D infrastructure - proven track record scaling systems by an order of magnitude or more, not just operating at scale someone else built.
2+ years of demonstrated experience managing team leaders, with a genuine track record of developing them.
Deep, hands-on AI engineering/ML expertise: LLMs, agentic systems, evaluation/benchmarking methodology, prompt/context engineering, and LLMOps.
Experience owning or closely partnering with large-scale data infrastructure - pipelines, storage, and especially web-scale crawling, caching, and indexing.
Experience taking a product from early stage to a clear, competitive market position, and scaling its infrastructure from millions to billions of API calls/month.

Requirements:
8+ years of engineering experience.
2+ years of hands-on experience with proxy infrastructure.
Deep, hands-on networking expertise - TCP/UDP, sockets, HTTP/HTTPS/SOCKS5, HTTP/2/3, DNS - at the protocol level, not the surface level.
Proven experience building (not just configuring or integrating) proxy or networking infrastructure - reverse proxies, rotation systems, IP reputation and quality management.
Working knowledge of proxy types - residential, ISP, mobile, datacenter - their characteristics, trade-offs, and failure modes.
Comfortable in the Linux networking stack: iptables, routing tables, network namespaces, connection tuning.
Experience with high-throughput, low-latency, high-scale systems, and the debugging skills to chase a problem down to a packet trace when needed.
Solid cloud infrastructure skills - Kubernetes, Docker, and IaC (Terraform) - to ship and operate what you build.
A genuine AI-native mindset - daily, expert use of AI-assisted development tools to move faster without sacrificing correctness.
Strong software engineering ability in Node.js, Rust, Go, or Python - you design and build production microservices, not just scripts and runbooks.
Experience with data infrastructure at scale - high-throughput pipelines and storage (nice to have).

Requirements:
Have 3+ years leading engineers - you know the difference between managing and leading
Have 5+ years hands-on backend engineering and you still write code in (Python/Node advantage)
Have 5+ years experience working in B2B SaaS environment and can demonstrate a strong understanding of Product
Have experience with Databases & Data Tools (PostgreSQL, DynamoDB, Amazon S3, Amazon SQS, Apache Airflow)
Are hands-on with the modern LLM stack: prompt engineering, fine-tuning, RAG, evaluation frameworks, and inference infrastructure
Have strong cloud-native background (AWS / GCP /Azure) - you've operated distributed systems in production, not just on paper
Have shipped high-scale, low-latency production systems and own the tradeoffs
Are a data pipeline native - you think in flows, volumes, and efficiency
Have built cloud-native systems in production, not just on paper
Hold a CS or Computer Engineering degree
Are energized by the startup pace
Adapt to changes quickly and know how to create clarity out of ambiguity