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Requirements:
Basic Qualifications
- Experience in one or more of the following: Big Data, DevOps, Security, Systems Administration, software development, cloud technology.
- Bachelor's degree in computer science, engineering, mathematics or equivalent, or experience in technical engineering.
- Speak, write, and read fluently in English, and have the ability to take direction in English.
- A passion for technology and for learning.

Preferred Qualifications
- Experience architecting, migrating, transforming or modernizing customer requirements to the cloud.
- Knowledge of presentations and whiteboarding skills with a high degree of comfort speaking with internal and external executives, IT management, and developers.
- Experience working with or for local Israeli enterprises (financial, telco, retail etc.).

Requirements:
What you'll need:
6+ years building and maintaining complex software systems.
6+ years backend experience, with a strong focus on production-grade systems.
1+ years JavaScript experience.
Hands-on experience with critical production systems - high availability, reliability, and scalability.
Familiarity with browser, networking, and security concepts.
Product, production, and growth mindsets.
Passion for solving technical challenges that directly impact users and operations.
Strong communication, collaboration, and problem-solving skills.
Can-do attitude with ownership mentality.
Professional-level spoken and written English.

It'd be cool if you also have:
Extensive experience with Node.JS.
Experience leading cross-team initiatives.
Frontend / React / Mobile experience.
Significant experience with databases/datastores (MySQL, Redis, ElasticSearch).
Experience from previous payments companies / projects.

Requirements:
Education: B.Sc. in Industrial Engineering,g Mechanical Engineering, Electrical Engineering, or a related technical discipline.
Experience: 3-5+ years of experience as a Production, Manufacturing, or NPI Engineer in a fast-paced, multi-disciplinary hardware environment.
Domain Expertise: Proven background working with high-precision electronics, RF systems, or advanced scientific control equipment.
CM Oversight: Hands-on experience managing external Contract Manufacturers (assembly lines, technical alignment, yield tracking, and performance reviews).
NPI & Legacy Management: Demonstrated ability to manage NPI handoff composition into volume production, as well as sustaining/legacy product management.
RMA Management: Proven track record running and dispositioning production-side RMA workflows.
Systems & Processes: Strong working knowledge of PLM/ERP/MES systems (e.g., Agile, Jira, Priority, NetSuite, SAP).
Communication: Excellent verbal and written English skills for effective cross-functional collaboration with R&D, Supply Chain, and external vendor leadership.
Nice-to-Have:
Lean Six Sigma: Lean Six Sigma certification (Green/Black Belt) or practical experience with Lean manufacturing tools and continuous improvement methodologies.

Requirements:
What you'll need:
8+ years of experience building backend systems in large-scale production environments.
Strong programming skills in Python, Java, Kotlin, or Node.js
Hands-on experience with cloud-native technologies (AWS, Kubernetes, Docker).
Proven ability to design and maintain high-scale distributed systems
Strong sense of ownership, autonomy, and accountability.
Excellent communication skills, with the ability to explain complex systems clearly to both technical and non-technical audiences - including direct collaboration with customers worldwide.

It'd be cool if you also have:
Experience with API Gateway architectures, schema/versioning strategies, or platformization efforts.
Familiarity with real-time data processing frameworks (e.g., Flink, Storm) and resilience patterns.
Background working alongside data science or machine learning teams.
Contributions to developer platforms, infrastructure services, or internal tools improving engineering velocity.

Requirements:
5+ years of strong backend and server-side development experience, building complex, highly scalable systems.
Proven experience with at least one general-purpose language (preferably Python, but not a must).
Strong product management skills, with the ability to gather and refine requirements from non-technical internal users.
A strong sense of ownership, with some DevOps experience and a willingness to develop, deploy, and run projects end-to-end.
Solid understanding of GenAI, LLMs and foundation models.
Strong familiarity with AI coding tools like Claude Code, Github Copilot, Cursor, or similar.
Hands-on experience with building AI-driven workflows, agentic frameworks, evals, RAGs, MCPs, skills, etc.
Experience working with public clouds (AWS / GCP / Azure).
Fluent in written and spoken English.

Requirements:
* Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
* At least 8 years of proven hands-on experience managing or working directly with data center and IT infrastructure (compute, networking, SAN/NAS, replication, backup/recovery, or similar).
* 5+ years of relevant product management experience, ideally in enterprise storage or infrastructure.
* Strong ability to translate complex technical and business challenges, and bring deep customer and business insight to product decisions, with a solid grasp of the needs of enterprise customers and service providers.
* Demonstrated experience collaborating with enterprise clients and large-scale accounts to deliver product releases and support successful deployments.
* Demonstrated initiative and self-motivation, with a track record of taking full ownership of projects from start to finish while requiring minimal guidance.
* Outstanding written and verbal communication skills, effective in both technical and business conversations. Ways to Stand Out:
* MBA or advanced technical degree.
* Prior experience at a storage or infrastructure vendor (Dell/EMC, NetApp, Pure, Vast, DDN, etc.).
* Experience partnering with global, enterprise-scale customers on infrastructure or data platform deployments, leading POCs, and beta programs.
* History of succeeding in product management within international or cross-cultural organizations.
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:
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of non-internship professional software development experience.
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design.
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.

Preferred Qualifications
- Master's degree or equivalent.
- Experience building server-side rendered web experiences (SSR) and performance-oriented UI rendering patterns.
- Experience with experimentation (A/B testing), analytics instrumentation, and metrics-driven iteration.
- Familiarity with AI/ML integration and generative AI applications.
- Experience with end-to-end SDLC ownership, including operations and on-call, monitoring/metrics, and incident response/RCA.

Requirements:
What you'll need:
6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.

Itd be really cool if you also have:
Experience with LangChain, LangGraph, LangFuse, or similar orchestration and observability tooling.
Hands-on experience with AWS Bedrock or other LLM provider APIs.
Experience designing or running AI evaluation frameworks (evals, LLM-as-judge, regression suites).
Familiarity with MCP (Model Context Protocol) or building tools for coding agents.
Experience with React, Next.js, or micro-frontend architectures.
Knowledge of Python for AI/data workflows.

Requirements:
Basic Qualifications
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience.
- Speak, write, and read fluently in Hebrew.
- 5+ years of experience in GTM strategy, business development, or technology sales in the enterprise technology sector.

Preferred Qualifications
- Experience with our AI/ML services (e.g. Amazon Bedrock, Amazon SageMaker, Amazon Quick, Kiro).

Requirements:
Who Are You?
7+ years of experience as a software engineer, with deep expertise in full-stack development, including strong command of modern backend technologies (Node.js, TypeScript) and frontend frameworks (e.g., React, Next.js).
Demonstrated track record as a go-to technical expert: you have led complex multi-system initiatives, set architectural standards, and influenced technical direction across teams.
Experience building customer-facing products and working closely with product managers and customer facing stakeholders. You think instinctively about user impact - not just technical correctness.
Hands-on production experience operating data systems at high scale - billions of records.
You are comfortable working with Redis, Kafka, SQS, Elasticsearch, MySQL, and Snowflake. You know how to design efficient data-access layers, work with sharded and partitioned systems, optimize schema and query performance under load, and build reliable ingestion and transformation pipelines.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Experience building products or workflows powered by LLMs or Agentic AI.
Experience enabling and mentoring engineers on your team.
Excellent communication and collaboration skills. You can discuss architecture with engineers, align on roadmap with product managers, and explain tradeoffs to non-technical stakeholders.
Experience using modern AI development tools such as Claude, GitHub Copilot, or similar to accelerate development and improve quality.
Proven ability to self-manage, work autonomously, and drive projects forward without heavy oversight.

It Would be Really Cool if you Also Have:
Deep experience with designing or maintaining high-scale data pipelines, including streaming, batching, or real-time enrichment workflows.
Experience with micro-services or micro-frontend ecosystem architectures.
Experience leading workshops, sharing knowledge internally, or driving community practices.
Experience participating meaningfully in recruiting - crafting interview questions, conducting technical interviews, and contributing to hiring decisions.

Requirements:
What you'll need:
5+ years of experience managing business critical teams.
IC experience as Staff+ Engineer or Tech Lead.
Experience overseeing big projects that have technical and/or business risks.
Experience working in performance critical environments (high scale, demanding SLAs).

It'd be cool if you also have:
Experience managing Staff+ engineers.
Experience working on customer-facing technical products (APIs, CLI tools, dashboards).
Experience interacting with clients and prospects.

Requirements:
What you'll need:
8+ years of production backend or data infrastructure experience, with at least 2 years at Staff Engineer or equivalent level
Excellent teamwork and communication skills, with a demonstrated ability to explain complex systems and facilitate collaborative solutions.
Deep experience with stream processing systems (Flink, Kafka, or equivalents) at production scale, including failure modes, recovery, and operational burden.
Strong distributed systems instincts: you think about correctness and reliability before you think about features.
Experience with data quality or observability infrastructure. You've built or owned the systems that keep a data platform honest.
Internal product mindset: you treat the teams you serve as customers and make deliberate choices about what to build vs. what not to build.

It'd be really cool if you also:
Have worked with data contracts, schema registries, or data governance tooling.
Have experience with JVM languages (Scala, Java, Kotlin) and big data DBs (Aerospike/elasticsearch/etc).
Have contributed to agentic or LLM-adjacent infrastructure. You understand what "data quality for agents" actually means in practice.
Have operated at a team technical anchor level in a small, high-scope team where breadth of ownership is the normv.

Requirements:
You'll do it using:

5+ years of proven experience architecting and delivering complex, scalable front-end ecosystems from the ground up.

Expert proficiency in React and TypeScript.

Deep understanding of modern state management (e.g., TanStack Query, Zustand) and UI performance optimization.

Hands-on experience leveraging AI-driven development ecosystems (Cursor, Claude Code, GitHub Copilot) to optimize engineering workflows.

Strong familiarity with applied AI concepts (GenAI, LLMs, AI Agents, Evaluation Metrics, MCP).


Advantage:

Experience with E2E testing frameworks (strong preference for Playwright).

Practical experience building UI for LLMs, including handling streaming responses, chat interfaces, and AI SDKs.

Full-stack capabilities (Python/Node.js microservices) and a willingness to work across the stack.

Familiarity with containerized environments and CI/CD (Docker, Kubernetes, Jenkins).


Youll Excel By:

Demonstrating extreme ownership and thriving in an autonomous, high-velocity environment.

Embracing new workflows and continuously pushing the boundaries of what AI coding assistants can achieve.

Solving complex technical challenges with clean, analytical, and maintainable solutions.

Maintaining a user-centric mindset when transforming advanced AI capabilities into intuitive experiences.

Requirements:
Basic Qualifications
- Education - Mechanical / Electrical engineer or practical Engineer with experience.
- High technical hands-on capability with out of the box solutions.
- Experience troubleshooting and debugging technical systems.

Preferred Qualifications
- Experience with IC testing.
- Knowledge of reliability stress methods.
- Experience in writing internal work procedures and customer facing reports.

Requirements:
Basic Qualifications
- Hands-on experience in RTL design using Verilog/System Verilog.
- Experience with chip design flows and gate-level simulations.

Preferred Qualifications
- Experience with DFT design and implementation (MBIST, JTAG/IEEE 1149.1, memory repair flows) and familiarity with industry-standard EDA tools such as Synopsys DFT Compiler and Tessent.
- Verification background including UVM testbenches, coverage-driven verification, FPGA, and emulator environments, with advanced scripting skills in Perl, Tcl, and/or Python.
- End-to-end chip development experience- from RTL design through synthesis, timing analysis, and physical design constraints to post-silicon validation, production, and memory fault debugging.