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You are a Senior AI Software Engineer looking to join a GenAI Infrastructure team and build production-grade GenAI capabilities and the infrastructure behind them. You will be a hands-on engineer focused on AI agents, RAG pipelines, tool-calling workflows, backend services, data access layers, evaluation, observability, and reusable GenAI infrastructure used across product teams. You will not be focused solely on model research or prompt design. Instead, you will be a strong software engineer who can design, build, ship, and operate reliable AI-powered systems in production.

A Day In Your Life
Build reusable infrastructure, SDKs, and internal frameworks for AI-powered product capabilities.
Design and implement AI agents, RAG flows, tool-calling workflows, and LLM orchestration pipelines.
Build production-grade GenAI services, APIs, and backend infrastructure.
Integrate LLM workflows with internal microservices, data platforms, vector search, and event-driven systems.
Design secure data-access patterns that enforce authorization, tenant separation, and user-level scope.
Implement evaluation, tracing, monitoring, and quality-control mechanisms for GenAI systems.
Improve latency, reliability, fallback behavior, cost efficiency, and production readiness.
Work on customer-facing AI experiences, including conversational and proactive agentic product flows.
Collaborate with backend engineers, product managers, data engineers, AI/ML engineers, and domain experts.

As an Algorithm and Applied AI Scientist (DSP), you will serve as the technical lead for an innovative project focused on advanced signal processing and data analytics applications. You will work with unique datasets from various signal-generating sources, researching and developing novel models, and analysing, maturing, and extracting features that have a significant impact on industrial manufacturers globally. In this role, you will be instrumental in defining project objectives, identifying customer value, and pushing the team toward successful outcomes. Joining our AI team offers ongoing professional growth in leadership, algorithm development, research, innovations, and technical data analysis.

A Day In Your Life:
Be the technical lead of an innovative project.
Develop a comprehensive understanding of industrial data by exploring its physical properties and the relationships among different data streams.
Oversee the full algorithm development cycle, spanning from initial problem definition to the deployment of production-ready feature-based AI models, SDLC starting from feature discovery that is being tracked by sensor behavior patterns.
Architect and build diverse predictive and anomaly classification models using sensor time-series and textual information.
You will gain a deep proficiency in the industrial world and the connection between datasets to generate actionable insights.
Utilize classic and cutting-edge technologies, such as Generative AI, transformers, TSFM, TGNN, deep learning, and traditional statistical methods, time-series, and textual data to generate actionable insights.
Partner with the product team and external customers to create data-driven solutions that address real-world business needs.

We're looking for a Product Data Analyst to help us find the opportunities hiding in our data and turn them into real product improvements.
You'll be part of the Analytics team, embedded in product decisions from early question to final recommendation. You will be tackling analytical questions, monitoring the metrics that matter, and surfacing insights that actually change how we build
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Collaborate with Analytics, Product, and Data teams to sharpen business decisions.
Initiate analyses and generate reports for feature tracking, experiments, and product health monitoring
Design A/B tests across our flows and processes to build better products
Analyze data using Snowflake, Python, and other platforms
Present key findings to stakeholders across the company, turning data into clear, actionable direction
Map new data domains and identify signals that push our product forward

As an Algorithm and Applied AI Scientist (DSP), you will serve as the technical lead for an innovative project focused on advanced signal processing and data analytics applications. You will work with unique datasets from various signal-generating sources, researching and developing novel models, and analysing, maturing, and extracting features that have a significant impact on industrial manufacturers globally. In this role, you will be instrumental in defining project objectives, identifying customer value, and pushing the team toward successful outcomes. Joining our AI team offers ongoing professional growth in leadership, algorithm development, research, innovations, and technical data analysis.

A Day In Your Life
Be the technical lead of an innovative project.
Develop a comprehensive understanding of industrial data by exploring its physical properties and the relationships among different data streams.
Oversee the full algorithm development cycle, spanning from initial problem definition to the deployment of production-ready feature-based AI models, SDLC starting from feature discovery that is being tracked by sensor behavior patterns.
Architect and build diverse predictive and anomaly classification models using sensor time-series and textual information.
You will gain a deep proficiency in the industrial world and the connection between datasets to generate actionable insights.
Utilize classic and cutting-edge technologies, such as Generative AI, transformers, TSFM, TGNN, deep learning, and traditional statistical methods, time-series, and textual data to generate actionable insights.
Partner with the product team and external customers to create data-driven solutions that address real-world business needs.

You will join the Deployment Platform team, which puts our 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 our 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.

As our AI Applied Researcher, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore, research, and develop cutting-edge solutions that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team, you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the technologies in the world, witnessing firsthand their impact on our customers.

A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Research, design, and build anomaly classification, predictive, insights, recommendations, and other types of models from various data sources, including sensor time-series data, textual data, images, and more.
You will Ensemble multi-modalities by exploiting and enriching the most from our data collections platform and feature extraction and store phases, using classic statistical methods, deep learning, Transformers, Graphs, Foundations Modules (as TSFM, Graph Transformer, TGNN), and any available technology to extract recommendations for taking real-world, life-changing actions.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Work with cloud-based big data platforms for training, distributed processing & experiments tracking (e.g., Metaflow, Grafana, Outerbounds, Databricks).
Partnering and contributing to modern technologies: LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.
As part of our hybrid working policy, you will be expected to work from the office at least twice weekly, which includes at least one day in Haifa.

We're looking for a Senior Director of Engineering to help scale how we build and own the core of business. This role sits at the center of our R&D organization, partnering closely with senior product and tech leadership to raise the bar on engineering culture, team structure, and platform ambiton.
We believe two things matter for every leadership role : leadership that sets the bar for excellence, builds high performing teams, and holds them accountable, and strategy that thinks several years ahead and turns ambitious plans into reality. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll:
Lead multiple engineering domains, owning the structure, standards, and performance of teams that build core product
Drive strategic initiatives that increase engineering leverage, so we can do more with smaller, sharper teams
Partner with senior product and tech leaders to shape how we build, not just what we build
Architect next-generation platforms that support our evolving product vision and scale with the business
Attract, develop, and retain high-performing engineers, holding a high bar at every stage of the hiring and growth process
Turn complex business problems into technical solutions that are clean, scalable, and built to last
Embed AI into how we develop and ship, using it to accelerate delivery and raise the quality ceiling

As our AI Applied Scientist, youll be at the intersection of advanced technology and meaningful impact with clear business cases. You will have access to real-time (RT) big data from multiple Sensors & Data sources, and a chance to discover, explore research, and develop cutting-edge models that directly impact industrial manufacturers around the globe. As part of the Applied AI/ML Science team, you will have the opportunity to continuously grow and learn while building and deploying advanced models directly into our products, and stay at the forefront of the world's technologies, witnessing firsthand their impact on our customers.

A Day In Your Life:
Own the algorithm lifecycle from problem definition and data analysis to prototyping and delivering production-ready models.
Combine classic methods with inference techniques: statistics, Time series, Deep learning, anomaly detection, Recommendation Systems, Transformers, and Inference to extract data-driven insights.
Research, design, and build Agentic applications on top of sensor time-series data, textual data, images, ML applications, and other various data sources.
Engage with customers and collaborate with our product team to develop innovative solutions utilizing new types of data.
Leverage modern technologies: work with cloud-based big data platforms for storage, distributed processing, LLMs and agents (GPT, Claude, Gemini), defining & building Gurdrails, reasoning chain as function call, planning, ML-based vectorization and embeddings, and stream analysis.

We are looking for talented engineers to help us develop a semiconductor platform based on a revolutionary architecture.

Key job responsibilities
The Linux Kernel development team is looking for a talented Linux kernel expert with experience in embedded systems, to join us in building the high-end AWS NITRO system. Youll have the opportunity to work on the top technologies powering the worlds largest cloud provider, in a dynamic, open, fast-paced environment. As part of your role you will develop kernel drivers and share your code with the Linux community. This is a rare opportunity to develop code that runs at such a high scale, with strict reliability and security demands.

We're looking for a talented Chip Design Engineer to join our Nitro team in Tel Aviv and help shape what comes next.

As a Chip Design Engineer on the Nitro team, you will take full end-to-end ownership of one or more critical IP blocks within the product, guiding them from micro-architecture definition through RTL design, debug, synthesis, timing closure, and final sign-off before tape-out. Your work will ship in silicon that powers us at global scale.
You'll partner closely with the Verification and Emulation teams to shape test plans, review coverage, and close gaps early in the design cycle. Beyond your own IP, you'll collaborate across disciplines with Product Definition, Software, Physical Design, and Verification teams to deliver a fully integrated, production-ready chip.

We are looking for a Senior Network SW Engineer to join the SW group and take a major part in redefining the future of our cloud.
Were searching for engineers with a passion for networking to develop SRD (Scalable Reliable Datagram). SRD is a high-performance, low-latency transport protocol used within Amazon Web Services (AWS) infrastructure to optimize network performance. SRD powers several high-impact, cutting-edge products, including on-demand ML and HPC platforms leveraging EFA, next-generation storage services built on EBS, and the future of AWS network traffic.

As a Senior Network Software Engineer on SRD team, your primary role will be to develop and optimize the implementation of SRD technology across AWS's network infrastructure. Your responsibilities will encompass designing, deploying, and maintaining SRD code-base, ensuring its reliability and scalability to accommodate the demands of various applications. An essential part of your role will involve conducting extensive network simulations to evaluate system performance under different conditions, enabling you to identify potential bottlenecks and inefficiencies. Using these simulations, you will troubleshoot network issues and implement robust solutions, leading to minimal data loss and latency. Leveraging your in-depth understanding of network protocols and AWS infrastructure, you'll refine and improve the SRD system's performance. Furthermore, you will be expected to mentor junior team members, leading projects to advance the SRD capabilities within the AWS environment. Staying updated with the latest industry trends and incorporating them into strategic network service planning.

We're looking for an exceptional senior Chip Design Engineer to join our Nitro team and help shape what comes next. You'll work alongside a world-class, fast-moving engineering team, take full ownership of critical IP blocks, and see your work deployed at a scale no other platform can match- powering hundreds of thousands of businesses across 190 countries.

If you want to build silicon that leads the cloud world, this is where it happens.

As a Senior Chip Design Engineer on the Nitro team, you will take full end-to-end ownership of one or more critical IP blocks within the product, guiding them from micro-architecture definition through RTL design, debug, synthesis, timing closure, and final sign-off before tape-out. Your work will ship in silicon that powers AWS at global scale.
You'll partner closely with the Verification and Emulation teams to shape test plans, review coverage, and close gaps early in the design cycle. Beyond your own IP, you'll collaborate across disciplines with Product Definition, Software, Physical Design, and Verification teams to deliver a fully integrated, production-ready chip.

Key job responsibilities
* Full ownership of one or more IPs within the product:
Micro-architecture definition.
RTL coding and debug.
Synthesis and timing closure.
Sign-off before tape-out.
* Supporting the Verification and Emulation teams: Test plan development, coverage review.
* Ensuring the chip meets quality and reliability standards.
* Collaborating with cross-functional teams, including Product Definition, Verification, Software, and Physical Design.

As a Principal Quality and Reliability Engineer, you will play a crucial role in ensuring Annapurna Labs' semiconductor products meet customer demands. Your responsibilities will include leading all Q&R activities for one of our IC product lines, chart the technical direction, build and lead a team of Q&R engineers, direct work with Annapurna's customers to jointly debug failures and reduce IC related failures, and support RMA analysis.
In this role you will have significant impact on, and be completely exposed to, the semiconductor production flow of all Annapurna Labs products, semiconductor testing methodologies and FAB process yield improvement activities.
This is a fast-paced role where you'll work with thought-leaders in multiple technology areas. You'll have high standards for yourself and everyone you work with, and you'll be constantly looking for ways to improve our products' overall performance, quality, and cost.

Were looking for an experienced & talented IT Infrastructure and Cloud Engineer to join our IT department and be responsible for our IT and Cloud Corporate Infrastructure. Youll be suggesting, implementing and deploying new IT solutions together with improving existing processes and maintaining our IT infrastructure, assuring that all of our systems are in optimal condition, providing the best service to our clients.
Responsibilities
Be responsible for requests from the field, related to our global corporate on-premise and cloud infrastructure. This includes servers, storage appliances, active network equipment, firewalls, cloud services, cloud automations, CI/CD and other initiatives.
Design and oversee the integration of core services and platforms such as AWS, Google Cloud and Workspace, Okta, Cloud Backups, Zero Trust Network Access (ZTNA), Secure Web Gateway, Cloud-based EDR and other cutting-edge technologies.
Spearhead the strategy, implementation, and governance of GenAI tools and platforms across the company, focusing on process improvement, building internal AI agents, and driving organizational AI transformation.
Lead the architectural design and deployment of scalable, reliable, and secure corporate infrastructure, emphasizing Infrastructure as Code (IaC) principles to manage on-premise and cloud environments.
Define network policies and procedures, including design, planning network new communication systems and monitoring to allow high quality service for our global offices.
Collaborating with our security team to implement technology and security policies, safeguarding our systems and data from potential threats.

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.