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We are seeking for an Infrastructure Developer for Embedded Hard rt Systems This role requires a talented and highly motivated software engineer to join our development team. The role includes working closely with hardware, system -level and low-level development, while collaborating intensively with hardware, testing and system teams. Development and maintenance of drivers and low-level software components in C / C ++ languages Implementation and maintenance of various communication protocols (such as UART, SPI, CAN, Ethernet, etc.). Work in Hard Real-Time environments and Bare Metal systems, including a deep understanding of operating systems (such as FreeRTOS, VxWorks) and without an OS. Analysis, writing and implementation of system requirements, including design and testing (unit, integration, system ). Real-Time performance optimization, system integration and integration of software and hardware components. Collaboration with system engineers, testing, hardware, FPGA and project management throughout the product life cycle - from defining the characterization to integration at the customer site. Writing development documents, including technical specifications, planning and testing. Beer Yaakov, Full-time, no hybrids

At Infinidat, a Lenovo company, we empower enterprises and service providers with cutting-edge storage platforms that redefine performance, reliability, and cyber resilience at scale. We are looking for a Tech Lead to join our System Validation & Verification team - someone who combines deep hands-on automation expertise with the leadership skills to drive technical direction, mentor engineers, and own end-to-end quality strategy for a complex, enterprise-grade distributed storage system. This role is centered on test design and development - the ideal candidate is someone whose craft is writing and owning tests for complex product features, and elevating a team to do the same at a high level. If you thrive at the intersection of architecture, code, and quality - and get energized by the challenge of making large-scale systems provably correct - this role is for you.

Responsibilities:

* Lead the technical direction of the automation group: define best practices, set coding standards, and guide architectural decisions for testing methodologies and new feature implementations
* Remain hands-on: actively write, review, and contribute to test code alongside the team, leading by example rather than by title
* Design detailed test plans for new features, and review and approve implementation designs proposed by team members for how those features will be tested
* Engage with R&D and Product from the earliest stages of feature development, providing input on testability, edge cases, and quality requirements before implementation begins
* Design and own test strategies for large, cross-cutting features involving multiple services and components working together
* Mentor and grow team members, conducting code reviews and elevating the team's engineering quality
* Work closely with development, product, and architecture teams to influence design decisions from a quality and testability standpoint
* Drive root cause investigations of complex, hard-to-reproduce issues - race conditions, timing-sensitive failures, and problems that only surface at scale
* Own release sign-off decisions - you'll have the authority to say "not good enough"
* Identify gaps in test coverage across service boundaries and drive initiatives to close them

This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production - owning outcomes end-to-end, including deployment, monitoring, cost, and business impact.

We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI.

What You Will Build
AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role - not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space.
Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requests as a risk to momentum. Use feature flags, canary releases, and rollback architecture to manage risk through isolation - not through avoidance.
AI-Augmented Engineering Workflow. Leverage AI-assisted development tooling (code generation, automated testing, architecture prototyping) as a core workflow multiplier. Evaluate and experiment with emerging AI tools and frameworks with direct hands-on engagement. Bring technical depth to AI fluency - architecture and capability tradeoffs, not surface-level awareness.
End-to-End Ownership. Own your work from design through production deployment, operational monitoring, and business impact measurement. Accountability extends beyond the feature to CI/CD pipeline health, observability, cost efficiency, and domain-level outcomes.
Architectural Decision-Making. Make pragmatic, timely architectural choices that balance modern AI and data technologies with reliability, cost, and delivery speed. Distinguish reversible vs. irreversible decisions and move forward without waiting for consensus on the former. Document decisions in lightweight ADRs and own the outcomes.
Cross-Functional Collaboration. Partner with product, design, infrastructure, and GTM teams to translate customer and business needs into technical solutions. Operate with business awareness - understand how your systems impact revenue, customer outcomes, and strategic priorities.