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we are looking for a Software Engineering Team Lead.
You will own the AI platform across all Sedric product lines - customer-facing policy configuration, internal tooling, and the architectural decisions that determine whether we scale reliably or expensively. Your responsibilities include:
Lead an engineering team - own output, growth, and retention
Build and evolve agentic systems that make high-stakes compliance decisions at scale: 99% accuracy, low cost, high throughput
Set guardrails, change management practices, and engineering procedures that meet the expectations of tier-1 financial institutions
Own customer-facing policy workflows and internal tooling for Technical Account Managers
Partner with the Head of R&D on technical direction and hiring

As a leading technology innovator, we push the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all.

As a company AI Software Engineer, you will develop and implement cutting-edge AI techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals.

In this position, you will be responsible for leading software development and implementation of the company AI Stack features within our AI Runtime (QAIRT) SDK, specifically Core software including Generative AI Inference Extensions. You will contribute to the efficient execution of advanced deep neural networks (DNNs), large language models (LLMs), and other modern AI architectures. You will also be responsible for supporting AI stack that optimizes runtime efficiency, latency and power consumption of AI applications running Machine Learning workloads on our low-power AI accelerators. The DSP core design work directly supports our NPU and GPU solutions, enabling optimized inference across diverse hardware platforms.

You will have the opportunity to demonstrate your passion for software design and development through your analytical, design, programming, and debugging skills.
Responsibilities
Develop real-time software for our AI DSPs to support the execution of the latest generative AI models on Snapdragon platforms

Develop and implement core components of our AI Stack runtime framework for inference on resource constrained AI systems, operating in low power, small memory footprint platforms

Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases

Debug complex issues, perform root cause analysis, and ensure high system reliability

Collaborate with cross-functional teams to deliver robust, scalable AI software solutions

Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team

Participate in design and code reviews

Working in global environment and collaborating inside the team and across other AI teams

Product Operator is a hybrid role for someone with Python, SQL, or other development experience who wants to grow fast in a startup environment. Youll support our engineering and data teams, work on client insights, and get hands-on with our business needs. Beyond coding, youll act as the right hand to the CTO, helping drive both technical and business initiatives.

Responsibilities
Support engineering and data teams with coding, testing, and analysis

Provide insights from client data to guide product and business decisions

Assist with product management tasks

Take ownership of cross-team tasks that require a technical mindset

Partner closely with the CTO to move projects forward across the company

We are looking for a motivated and skilled Software Engineer to join our growing team. This is an exciting opportunity for someone with a strong technical foundation who enjoys working with diverse technologies, solving complex technical challenges, and contributing to impactful, real-world products. You will collaborate with cross-functional teams to design, develop, and maintain scalable software solutions while continuously learning and adopting new technologies.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.

Your Impact
AI Agent Development

Design and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management.

Implement reinforcement learning techniques to enhance decision-making capabilities of AI agents.

AI Integration

Build and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM).

Use frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing.

Data Processing and Pipelines

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently.

Optimize data handling to improve speed and accuracy of AI agents.

Security and Compliance

Implement authentication and authorization mechanisms to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling.

Cloud Infrastructure and Scalability

Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.

Leverage containerization (Docker, Kubernetes) for efficient deployment and management.

Testing and Optimization

Develop and execute unit, integration, and performance tests for AI-driven systems.

Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.

Collaboration

Work closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements.

Participate in code reviews, design discussions, and architecture planning to drive innovation.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

We are looking for a highly analytical, detail-oriented Innovation Expert to join our Open Innovation team. This role is ideal for an individual contributor operating at the intersection of deep tech, the startup ecosystem, and academia, with strong technology analytical skills, clear communication, and a foundational background in computer architecture research.

In this role, you will drive our external innovation strategy by managing academic research collaborations, scouting early-stage deep-tech startups, and conducting technical due diligence.

Key Responsibilities
Academic Cooperation & Research Partnerships: Identify and build direct collaboration agreements with world-class professors, research labs, and universities. Facilitate joint research projects, tech-transfer initiatives, and track academic spin-offs.
Startup Scouting & Ecosystem Mapping: Actively identify, source, and map early-stage deep-tech startups and emerging tech companies globally within the companys strategic domains.
Technical Due Diligence: Evaluate startup technologies, product-market fit, and team capabilities. Analyze technical validity and assess how external innovations align with our internal roadmaps.
Ecosystem Analysis: Conduct deep-dive analyses of startup ecosystems, venture capital trends, and academic spin-offs to identify high-potential investment and collaboration opportunities.
Investment & Collaboration Support: Synthesize technical and commercial findings into clear, structured scouting reports, investment tech memos, and presentations for senior leadership to drive partnership or investment decisions.
Cross-Border Collaboration: Act as a bridge between startup founders, academic innovators, and internal global teams (including European and China-based business units) to facilitate joint POCs, or investment reviews.
Track Tech Domains: AI infrastructure, advanced semiconductors, hardware-software co-design, and AI data movement.

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next-generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage, and networking at large scale. We aim to drive innovation and deliver software-defined infrastructure and algorithms for HPC, AI/ML, and Big Data applications.
We are looking for an outstanding Research Team Lead with deep hands-on expertise in large-scale distributed systems, AI framework infrastructure, and performance optimization on custom accelerators. If you are a visionary technical leader, a skilled communicator, and a team builder who thrives at the frontier of systems and AI research - you're welcome on board.

What Will You Be Doing?
Lead and grow a world-class team of researchers and engineers working on distributed AI infrastructure and systems software.
Architect and own the software infrastructure enabling distributed training and inference on Huawei's custom accelerator hardware (e.g., Ascend NPU).
Drive research and development on communication libraries, runtime systems, memory management, and graph execution & synchronization at scale.
Optimize end-to-end performance across large-scale clusters, covering both scale-up (multi-device) and scale-out (multi-node) configurations.
Design and implement high-performance communication backends and collective operations (AllReduce, AllGather, broadcast) for distributed training workloads.
Collaborate cross-functionally with hardware architects, compiler teams, and framework engineers to co-design hardware-software solutions.
Publish and present research findings at top international venues (NeurIPS, EuroSys, SC, MLSys, OSDI) and represent the team externally.
Mentor engineers and researchers, conduct performance and growth reviews, and shape team culture and technical direction.
Partner with top academic institutions and open-source communities to advance the state of the art in distributed AI systems.

*Part-Time or Full-Time Opportunity

In this job opening, we are seeking a highly motivated and visionary researcher to join our team focused on chiplet-based computing systems. This role involves research and development in chiplet-based architectures, aiming to overcome performance and scalability limits of traditional compute platforms.

Responsibilities:
Conduct cutting-edge research on the co-design of communication and computation for wafer-scale systems. On the communication side, the work focuses on architecting Networks-on-Chip, providing scalable, high-bandwidth, and ultra-low-latency interconnects that efficiently span multiple dies and support fine-grained data movement. On the computation side, the research emphasizes optimizing and mapping training and inference workloads to fully exploit wafer-scale resources, improving performance, scalability, and energy efficiency through intelligent task placement and scheduling.
Investigate various aspects of system design, including:
Network-on-Chip design, further including Topology exploration, routing algorithms, and protocol/flow-control design to support high-throughput collective communication, low-latency synchronization, and efficient model/data parallelism
Expressing and Mapping LLM Parallelism to Wafer-Scale System that simplify LLM parallelism (e.g., tensor, pipeline, and data parallelism) and efficiently map training and inference workloads onto wafer-scale system

We are looking for an experienced Tech Lead to lead a team of 3-5 software engineers developing innovative database security and data protection solutions for enterprise platforms.

This is a hands-on technical leadership role focused on cybersecurity, data security, and advanced software engineering. The successful candidate will combine deep security expertise with strong software architecture skills to define technical direction, lead engineering execution, mentor developers, and build enterprise-grade security solutions.

The role requires strong technical ownership, the ability to solve complex security challenges, and close collaboration with security researchers, product teams, customers, and engineering organizations. Occasional travel may be required for technical discussions and customer engagements.

Responsibilities
Lead and mentor a team of 3-5 software engineers, providing technical guidance and driving engineering excellence.
Define software architecture, technical strategy, and development direction for database security products.
Design and develop advanced cybersecurity and data security solutions for enterprise environments.
Lead security architecture discussions, technical design reviews, and code reviews.
Translate complex security requirements and research concepts into practical, scalable software solutions.
Drive secure software development practices across architecture, design, implementation, and deployment.
Solve complex technical challenges related to security, reliability, scalability, and performance.
Collaborate with security researchers, product management, and cross-functional engineering teams.
Participate in customer-facing technical discussions and occasional international travel.
Remain hands-on and contribute to critical software components and technical decisions.

We are looking for a Principal Engineer with deep expertise in database internals, system architecture, and hardware-aware performance optimization.
This role is responsible for defining and driving advanced database performance solutions by understanding and improving the interaction between database engines, operating systems, and modern hardware architectures.
The ideal candidate is an experienced technical leader with a strong background in database systems, performance engineering, and computer architecture. The candidate should be capable of leading complex technical initiatives, influencing architectural decisions, and developing innovative solutions for next-generation database platforms.
This is a hands-on technical leadership role requiring expertise across database kernels, query execution, transaction processing, memory systems, and low-level performance optimization.

Responsibilities
Define and drive technical direction for database performance optimization and hardware-aware database architecture.
Lead the design and implementation of advanced database optimizations focused on scalability, efficiency, and workload performance.
Solve complex performance challenges across the full system stack, including database engines, query execution, transaction processing, concurrency control, storage engines, operating systems, and hardware platforms.
Design and develop optimizations leveraging modern hardware architectures, including multi-core CPUs, large-memory systems, NUMA platforms, CXL memory, RDMA networking, and advanced storage technologies.
Improve database execution engines, caching mechanisms, memory management, storage systems, and workload scheduling.
Analyze system behavior and identify bottlenecks using profiling, tracing, hardware performance counters, and low-level performance analysis.
Develop benchmarks, workload models, and methodologies to evaluate scalability, efficiency, and architectural tradeoffs.
Collaborate with database kernel, infrastructure, and engineering teams to influence architecture decisions and deliver high-impact improvements.
Mentor senior engineers and contribute to building technical expertise across the organization.
Drive innovation through research, prototyping, technical analysis, and architectural improvements.

We are looking for an ATE Engineer to join our multidisciplinary team in central Israel.
The role involves developing and implementing complex automated test solutions, from requirements analysis through direct integration with hardware and Automated Test Equipment (ATE).
Key Responsibilities:
Translate Test Requirements Documents (TRD) into automated Test Sequences/Scenarios using NI TestStand or OTM (ORION).
Develop, maintain, and enhance automated test sequences and deploy them in laboratory environments.
Integrate measurement instruments and communication protocols with ATE systems, perform debugging, and support troubleshooting activities.
Develop software components and DLLs in C# or C for hardware communication, when required.
Work closely with Hardware, Electronics, and Integration teams, including reading and interpreting electrical schematics.

We are looking for an experienced Software Engineer (4+ years) to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development program.
In this role, you will act as an AI Champion and Technical Mentor within the clients R&D organization. Your mission is to help development teams effectively integrate AI tools, agentic coding workflows, and best practices into their daily software development lifecycle (SDLC). You will help guide teams through AI adoption, help overcome resistance, and ensure AI delivers real value.
This is not a feature-delivery or coding-focused role, especially in the early stages, the position is centered on enablement, training, and integration, working closely with teams to embed AI development tools into real workflows and support the organizations AI transformation.
This is a high-impact role focused on technical enablement, AI expertise, and effective collaboration with development teams, and intended for experienced engineers who actively use AI in their day-to-day development work and are looking to influence how teams work, rather than for junior profiles or engineers seeking a purely coding-focused position
What Youll Do:
Help drive adoption and optimization of Claude Code and/or similar Agentic coding tools
Support software and QA engineers, answer technical questions and help unblock teams
Stay on the cutting edge of AI releases and best practices, turn your learnings into shareable assets (custom rules, agents, skills, demos, playbooks, etc.)
Measure impact, identify gaps and improvement opportunities across the SDLC
Help defuse resistance to change with patience and empathy
Partner with DevOps, architects and management to track and optimize AI utilization.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.