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Required Senior SoC Product Engineer, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
Responsibilities
Develop and implement strategies for high volume manufacturing of SoC products, including troubleshooting, ATE test coverage optimization, DPPM reduction, test cost reduction, power and performance assurance, and product data integration and correlation between system, ATE, and SLT.
Drive interactions with wafer fab and OSATs, own and drive checkpoints for key quality metrics.
Drive volume ramp and mass production through test program releases, volume data analytics, lot disposition, extended test time reduction, yield improvement, and RMA handling.
Support setup and maintenance of test, diagnosis, and yield analysis infrastructure, including Return Merchandise Authorization (RMA) support.
Collaborate with cross functional teams across the globe including ATE and SLT Test Engineering, Quality and Reliability (Q&R), Packaging, Supplier Management and Operations to build, deploy, and maintain a high volume manufacturing screening solution.

Key job responsibilities
* Design and implement advanced Design-for-Test (DFT) architectures for complex semiconductor platforms.
* Develop high-quality test and debug patterns ensuring robust performance.
* Conduct comprehensive static timing analysis across multiple DFT modes.
* Verify intricate DFT logic and components with precision and creativity.
* Support silicon bring-up and device diagnostic processes.

Your day will be filled with complex problem-solving and collaborative innovation. You'll work alongside world-class DFT engineers in a dynamic environment, developing semiconductor technologies that support global cloud infrastructure. Our team thrives on creativity, technical excellence, and continuous learning.

We are looking for a Logic Design Engineer to join the ride as we spearhead the next revolution in electronics!.

Our Logic Design team builds the on-chip monitoring IP at the heart of our product - digital blocks that ship inside some of the most advanced chips in the industry. Were growing the team and looking for a Logic Design Engineer to take ownership of that logic, working alongside circuit, verification, physical design, EDA, and AE engineers. A strong fit if you enjoy hard digital design problems in a collaborative, technically demanding environment.

Responsibilities
Define and implement digital logic micro-architecture - in plain English, diagrams, and SystemVerilog.
Verify design quality against industry standards using static analysis tools (Lint, CDC, RDC).
Work with Circuit Engineers to turn low-level circuit designs into the well-behaved, insightful agents at the core of the proteanTecs solution.
Work with Verification Engineers to simulate and debug the digital logic.
Work with Physical Design Engineers to ensure correct implementation of our special circuits.

we are establishing a strategic R&D center in Israel to drive the development of complex semiconductor chips that solve the critical 'data bottlenecks' enabling the future of AI at scale. As we expand our presence in Israel, we're seeking a talented Junior Design Verification Engineer to help build our local engineering powerhouse from the ground up. This is an exciting opportunity to take on meaningful ownership in a new site, developing the verification environments that ensure our next-generation AI silicon performs flawlessly.
As a Junior Design Verification Engineer, you will be a vital contributor to the quality and reliability of our Israel R&D center. You will work on the front lines of functional verification, developing testbenches and environments that validate high-performance digital blocks, subsystems, and full-chip designs. You will tackle complex verification challenges that ensure our connectivity solutions meet the rigorous demands of the world's largest AI clusters. If you thrive on solving technical puzzles and want to play a key role in delivering cutting-edge AI infrastructure connectivity, this is your opportunity.
Key Responsibilities
Verification Environment Development
Contribute to the design and development of ASIC verification environments, focusing on unit-level and subsystem functional blocks
Develop and maintain SystemVerilog/UVM-based components including traffic generators, monitors, and checkers to ensure robust testing
Execute detailed verification plans for challenging digital designs, ensuring all functional requirements are met and verified
Coverage & Quality Assurance
Implement functional coverage models and analyze results to identify gaps in the verification process
Drive designs toward 100% verification closure through comprehensive test development
Contribute to verification methodology improvements and best practices
Debug & Cross-Functional Collaboration
Work closely with design engineers to identify, root-cause, and resolve complex hardware bugs early in the development cycle
Apply analytical skills and debugging techniques to solve intricate verification challenges
Collaborate effectively in a fast-paced, team-oriented R&D environment.

We are looking for highly motivated engineers who love the challenges and the opportunity of a small company. Join us and be a part of a small and dynamic team, which revolutionizes the parallel processor architecture.

We're looking for a VP R&D to build both the technical foundation and the engineering organization behind that platform. This is not pure people management, and it's not a chief-architect role in disguise. It's a rare combination: a deeply technical leader who can challenge the strongest engineer in the room on architecture, and who also builds an organization where talented people grow, decide independently, and own outcomes end to end.



What You'll Own

Technical direction: Define architecture and technical strategy with the CTO, Product and AI leadership. Make real tradeoffs between speed, simplicity, reliability and long-term scale. Stay deep enough to lead architecture reviews, surface hidden risks, and tell the difference between an impressive demo and a dependable production system.
An enterprise-grade agentic platform: Agent orchestration, planning and tool use governed knowledge and policy representation retrieval, context and memory evaluations human review and escalation permissions, identity, security and auditability reliability and observability cost, latency and model performance enterprise integrations.
The R&D organization: Design the structure for the company's next stage. Recruit exceptional engineers and engineering leaders at a consistently high bar. Grow managers and senior ICs who own major domains independently. Set clear expectations, feedback and performance standards - and build a leadership bench so the org doesn't depend on a handful of people.
Autonomy with accountability: Define outcomes, decision boundaries and interfaces, then push decisions as close to the problem as possible. Autonomy that produces better and faster decisions - not ambiguity, duplicated work, or diffused responsibility.
Velocity and quality together: An operating model that moves fast without normalizing instability. Better planning, testing, deployment, observability and incident learning. AI-native development as real leverage for every engineer, with clear standards for security, correctness and human judgment.
Business impact: Shape the roadmap with Product rather than receiving requirements. Join strategic customer conversations where technical leadership builds trust and unblocks adoption. Operate as a company leader, not only a function leader.

Own the internal DevEx platform roadmap backlog, translating organizational strategy and R&D needs into prioritized initiatives that deliver measurable value across the R&D organization. Work closely with internal customers within R&D, aligning tightly with the External developer PM
Key Responsibilities
Requirement Definition (the core of the role): Create and own the requirements for the platform solutions we build for our developers. You continuously synthesize and prioritize four inputs into a clear, coherent product direction:
Strategic priorities - the direction set with the Chief Architect on where platform investment should go.
Organizational needs - the recurring challenges and demands surfaced by R&D divisions and their leadership.
User feedback - direct input from the internal developers who use the platform day to day.
Architectural guidance - professional input from Architects, both within the Chief Architect Office and across the product-specific architecture teams.
Platform Product Ownership: Serve as the product lead for the internal platforms and tools our engineering teams build for our developers - for example, our agentic developer platform, among a growing set of developer-experience capabilities. Define what each should do and the outcomes it should deliver, and keep the portfolio aligned to a shared vision.
Prioritization & Roadmap: Maintain a clear, well-reasoned view of what matters most and why, so platform teams always know what to build next and the organization understands the rationale.
Cross-Functional Alignment: Drive the work processes that turn inputs into shipped platform capabilities, partnering across engineering managers, directors, and architects. Set direction, align stakeholders, and keep initiatives moving forward.
Feedback & Impact: Establish durable channels to collect and synthesize developer feedback and adoption signals, feed them back into the requirements, and demonstrate the platform's impact on developer productivity.

You will join the Deployment Platform team, which puts technology directly in the hands of customers, field technicians, and partners. As an AI-Native mobile engineer, your primary development framework is Flutter (with native iOS and Android used when needed), building the mobile application central to field deployment. You are also comfortable across the full stack to ensure end-to-end feature delivery. Most importantly, you will shape the next generation of agentic installation experiences that define how industrial AI reaches the factory floor. This is a high-impact role at the intersection of mobile, IoT, and AI.
A Day In Your Life:
Design, build, and maintain high-quality, cross-platform mobile applications for iOS and Android using the core Flutter/Dart stack.
Lead the design and shipment of agentic-first workflows for guided installation, leveraging LLMs (Azure OpenAI, Gemini) to assist technicians and automate decision-making in the field.
Implement complex IoT/Hardware integration features, including NFC provisioning, AR field tools, and indoor positioning/navigation.
Contribute to backend and frontend services/APIs to ensure seamless, end-to-end feature delivery.
Architect and maintain a scalable, modular monorepo, ensuring robustness through strong state management (BLoC/RxDart) and comprehensive test coverage.
Collaborate with product and design teams to deliver exceptional UI/UX, including adaptive and RTL-aware layouts.

We are looking for a Backend Tech Lead to drive the architecture and development of our AI-powered language learning platform. In this role, you will design and implement backend systems that directly impact millions of learners worldwide. You will architect scalable services that power real-time AI conversations, ensuring low-latency performance and reliability while building the foundation for our next generation of language learning features.
What Youll Do:
Design, develop, and maintain high-performance backend services and APIs (REST and gRPC) that power AI-driven conversational experiences.
Build and optimize asynchronous Python applications capable of handling real-time audio/text processing at scale.
Ensure seamless, low-latency integration between mobile and web clients and our AI backend platform.
Drive technical decisions on system architecture, focusing on low latency and fault-tolerance.
Collaborate with AI/ML, mobile, DevOps, and product teams to deliver end-to-end solutions that delight our users.
Work within CI/CD workflows to ensure smooth deployments and maintain high code quality standards.
Optimize system performance and resource utilization while maintaining reliability SLAs for our growing user base.

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.
This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability.
How will you make an impact?
AI Quality Strategy:
Define and lead all AI-augmented quality initiatives across the organization
Deploy LLM-powered test generation, triage, and root-cause analysis tooling
Build frameworks for validating AI/ML model outputs and non-deterministic behaviors
Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)
Champion responsible AI testing practices, coverage standards, and governance models
Automation Engineering:
Own the full automation strategy across UI, API, and integration layers
Architect scalable, maintainable test frameworks
Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)
Establish coverage KPIs, flakiness SLAs, and automation ROI metrics
Lead adoption of self-healing and AI-assisted test maintenance
Performance Engineering:
Lead performance and load testing strategy at enterprise scale
Define SLOs/SLAs and partner with SRE on reliability thresholds
Design continuous performance validation integrated into delivery pipelines
Drive root-cause analysis for regressions, bottlenecks, and latency spikes
Oversee toolchain including k6, JMeter, Gatling, and APM integrations
People & Org Leadership:
Lead and grow teams of automation engineers, performance engineers, and architects
Set technical direction, OKRs, and career ladders for the quality engineering org
Hire senior ICs and architect-level talent; build succession depth
Foster a culture of ownership, engineering craft, and continuous learning
Partner cross-functionally with Product, DevOps, and R&D leadership.

We are looking for a hands-on DevOps Engineer with a strong cloud-native mindset to build, maintain, and evolve our highly scalable, highly-available cloud infrastructure. This role is pivotal in driving operational excellence, security, and automation across our entire engineering organization. You will promote communication, integration, and collaboration to significantly enhance our software development productivity and reliability. You'll work closely with engineering and product teams to streamline delivery, enforce platform standards, and enable a high-velocity development environment-all while keeping reliability and security top of mind.
Responsibilities:
Design, Automate, and Manage complex cloud infrastructure on AWS using best-in-class Infrastructure as Code (IaC) practices.
Lead the operation and enhancement of our production Kubernetes environments (EKS), focusing on automation, security, observability, and seamless CI/CD integration.
Drive continuous improvement across platform tooling, developer experience, and operational processes to meet our ambitious performance and uptime goals.
Implement and enforce security-first infrastructure patterns, including strong IAM, network segmentation, and secure secrets management.
Actively contribute to high-level technical design discussions and cross-functional architectural decision-making, ensuring solutions align with long-term platform strategy.
Drive AI-Powered Automation: Design, build, and deploy infrastructure for autonomous AI agents and agentic flows, integrating AI tooling directly into developer platforms and CI/CD pipelines.
Architect AI Platform Infrastructure: Establish reliable, scalable, and secure AI/DevOps orchestration frameworks to enable continuous deployment and runtime management of AI-driven tools.

Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.


Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.

We are looking for a Lead DevOps Engineer to join our team as our first dedicated infrastructure hire. You will play a foundational role in architecting and scaling the engine that powers our cloud services and on-premise hardware deployments.

This is a position with real ownership. You aren't just managing servers; you are designing the delivery, monitoring, and security standards for a product that must thrive in both high-scale cloud environments and strictly disconnected, air-gapped networks.

Requirements
What Youll Do

Build the Foundation: Architect and maintain our core cloud infrastructure (IaC) and CI/CD pipelines, ensuring a seamless path from code to production.
Universal Observability: Design and deploy a "conservative" yet powerful logging, monitoring, and alerting stack (e.g., Prometheus, Grafana, Loki) that works similarly in the cloud and in disconnected on-prem environments.
Infrastructure as Code: Develop portable Pulumi
On-Prem & Air-Gapped Strategy: Create the systems and tooling required to package, deploy, and update our software on customer environments with zero internet access.
Customer Infrastructure: Lead the deployment of cloud-based gateways and managed services for our enterprise clients, ensuring high availability and robust security.
Security & Encryption: Implement and manage critical security infrastructure, including mTLS, CA-signed certificate management, and hardened Linux service configurations.
Collaborate with R&D: Work closely with our networking and hardware engineers to bridge the gap between low-level connectivity and scalable cloud architecture.

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

We are seeking an energetic and versatile Principal Software Engineer to join our elite team responsible for building our Identity Directory Service and User Management platform. In this role, you will be a core technical authority using AWS architecture, AWS CDK, and .NET to design, develop, test, secure, and deploy high throughput, production ready cloud services from planning to production.
Working in full collaboration with security architects, product managers, and cross functional development teams, you will produce complex and advanced SaaS services that satisfy demanding scalability, security standards, and Non-Functional Requirements (NFRs).
Your Impact
System Architecture & Design: Lead the architectural design and system implementation of cloud-native, distributed microservices using AWS and .NET following secure-by-design principles.
SDLC Mastery: Practice all aspects of the software development lifecycle within an agile, continuous-delivery environment.
Research & Innovation: Spearhead research into modern cybersecurity mechanisms, evaluate emerging tech stacks, and pioneer cut-edge solutions to solve complex platform bottlenecks.
Technical Mentorship: Drive engineering excellence through code reviews, design discussions, and active coaching to uplevel engineers across the team.
Quality & Scalability: Participate in continuous and iterative engineering cycles with a heavy focus on code quality, testability, supportability, performance, and cost optimization.