לוח משרות דרושים AI Engineer

As a Senior Developer, youll join our Product Team and play a key role in architecting and developing AI-driven building operating system. Youll work with the team to plan, shape, and build platform components, AI workflows, and new product features. You should feel comfortable collaborating in a product squad and be excited about the new era of AI-native SDLC, using coding agents to move the needle independently while keeping productivity and simplicity in mind.

About you

An ideal candidate is humble and open-minded, while staying skeptical and willing to challenge assumptions. You have strong full-stack engineering skills and experience reasoning about complex systems, evolving architecture, and the importance of collaboration, communication, and product sense. You excel at working independently and as part of a team, and you feel comfortable asking for help when you get stuck.

Responsibilities

Plan, design, and ship agentic workflows that automate operational processes with human oversight built in.
Work cross-functionally with product, design, operations, and business teams to deliver AI features that solve real problems.
Own feature development end-to-end: from ideation and discovery, through spec writing, development, testing, launch, and iteration.
Push the limits of coding agents to increase developer velocity and democratize development for non-coders.

We're looking for a AI Research Scientist to join us in spreading the power of our company and push the boundaries of AI in cybersecurity. You'll be at the forefront of developing novel AI models - focusing transformers and LLMs - that advance how cybersecurity operates. Contribute to the wider AI and cyber communities through publications and conference presentations, establishing our company as a thought leader at the intersection of AI and cybersecurity.
WHAT YOULL DO
Develop and research novel AI models, focusing on transformers and deep learning. Lead mid- to long-term projects aimed at advancing AI-driven features in the cybersecurity domain for our company products.
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay informed about cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions accuracy, efficiency, and scalability.
Collaborate with engineering teams to design, build, and maintain production pipelines. Work closely with the Security Research and Product teams to define research goals.
Publish research findings and AI thought leadership content and present at leading conferences such as NeurIPS, ICML, or CVPR.

We are currently seeking an experienced Full-Stack Engineer to join our team.
Role & Responsibilities:
You will be delivering scalable web applications from idea to production , while taking care of all aspects of software development-from technologies and security to scalability and reliability processes.
End-to-End Ownership: You will have full ownership of your features from the architecture level, through design, and finally implementation.
Cloud Infrastructure: Be part of the design, maintenance, monitoring, and troubleshooting of our cloud applications and infrastructure.
Technical Excellence: Drive technical excellence, high product quality, innovation, and timely delivery in an agile, production-critical environment.

Join our companys Content Safety team as a Staff AI Scientist, where youll build the intelligent infrastructure that keeps our global platform secure. We're looking for a specialist to design and deploy production-grade GenAI solutions that moderate content at scale. From pioneering automated labeling workflows to securing AI-generated outputs, your work will define the safety standards for every product in the company portfolio.
Responsibilities
Architect Robust Moderation Systems: Lead the design and deployment of sophisticated, multi-modal content moderation engines to detect and mitigate abusive content across our companys diverse product ecosystem.
Drive LLM Strategy: Direct the fine-tuning and optimization of state-of-the-art Transformers and Large Language Models (LLMs), balancing high-precision accuracy with production-scale efficiency.
Pioneer Agentic Workflows: Research and integrate advanced GenAI patterns-including Retrieval-Augmented Generation (RAG) and Agentic AI-to revolutionize automated data labeling and complex classification taxonomies.
Cross-Functional Leadership: Partner closely with ML Engineers, Product Leads, and Policy Experts, to help ensure AI systems aren't only technically superior - but also ethically grounded and compliant with global safety standards.
Technical Evangelism and Research: Act as the teams North Star by staying at the bleeding edge of AI research, translating academic breakthroughs into practical, "production-first" content safety strategies.
Communication and Governance: Standardize high-quality documentation and model governance. You will translate complex technical architectures into clear, actionable insights for both executive stakeholders and technical peers.
Team Upskilling and Mentorship: Serve as a force multiplier by mentoring junior and senior scientists, conducting rigorous code/design reviews, and fostering a culture of technical excellence.

Come join the company team as a Staff AI Engineer.
Our Data Exchange group is responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all our company products.
You will utilize your skills to help develop and maintain backend services leveraging AI and machine learning models, using both analytical algorithms and deep learning approaches, to acquire data from financial institutions on behalf of our users.
Responsibilities
Lead and apply best practices in AI driven software lifecycle management, from ideation, through development and evaluation to production deployment.
Build a backend service with AI in its core at scale (millions of users and requests daily)
Collaborate with stakeholders to define success criteria and align model metrics with business goals
Work side-by-side with product managers, business analytics, data scientists, and backend engineers in enabling AI solutions for business use cases
Explore the state-of-the-art technologies and apply them to deliver customer benefits.

we are looking for a AI Team Lead.
As our AI Team Lead, you will sit at the intersection of cutting-edge research and production engineering, guiding a high-performing team of Data Scientists and Engineers. This is a deeply hands-on leadership role where you will drive the end-to-end lifecycle-from initial research and PyTorch training to deploying sophisticated multi-modal AI (Text, Image, Audio, and Video) in high-throughput environments. Join us in building the future of responsible AI adoption and digital integrity.
Responsibilities:
Manage and grow a high-performing team of AI researchers and engineers, fostering technical excellence.
Drive the design and training of multimodal models applications (Text, Image, Audio, Video) using PyTorch.
Own the AI roadmap from initial concept to scalable, high-throughput production.
Partner with Product, Backend, and Security teams to integrate AI solutions globally.
Stay at the forefront of GenAI/LLM research to continuously improve our detection engines.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on our company Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.
You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on our company NPUs.
What will you do:
Develop and enhance AI graph compiler components targeting our company NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into our company NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.

In this role, you will be a key contributor to the design and implementation of our companys AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the AI Graph Compiler software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

In this role, you will be a key contributor to the design and implementation of our companys AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our companyNPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the AI Graph Compiler software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

In this role, you will be shaping the future of our companys AI software stack for Neural Processing Units (NPUs). You will lead software architecture, define performance-critical components, and enable efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
We are seeking a high-impact motivated Software Architect to join our team and help shape the future of our advanced neural network AI Software Toolchain over our companys AI computing processors.
Responsibilities
Lead Software Architecture specification and supervise design for the most advanced Software Toolchain handling state-of-the-art Neural Processing Unit operation.
Design and promote holistic software solutions incorporating various aspects of NPU handling: from network retraining, graph compiling and network inference execution on the embedded systems.
Collaborate proactively with Product, Architecture, VLSI and Software teams to promote software leadership over various markets and compute SoCs.
Explore and translate state-of-the-art neural network and AI applications requirements into software architecture flows, encompassing hardware, software, tools and other components.
Evaluate architecture proposals, internal and external IP features and provide influential and inspirational leadership across hardware and software to align all parties to a common vision of architecture & technology development.
Represent our company with high technical credibility in customer meetings, appropriately incorporating feedback.
Boost velocity of development teams by providing technical guidance and by constantly looking ahead to anticipate and resolve future challenges.
Conduct experiments, invent and drive development of supporting tools such as simulators, models, profilers, and other methods as required.
Engage with engineering leadership and product planning stakeholders to develop technology roadmap.

In this role, you will be a key contributor to the design and implementation of our companys Edge AI software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the Edge AI software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

We are seeking a skilled Backend Engineer to join our team and implement advanced AI solutions in our travel and expense management products. The ideal candidate will have strong backend engineering expertise and enthusiasm for working with cutting-edge AI technologies.
You'll be responsible for designing and implementing backend services that integrate AI capabilities including large language models (LLMs), retrieval-augmented generation (RAG), and conversational interfaces into our consumer-facing products. This is an opportunity to expand your expertise into AI while leveraging your strong engineering foundation.
What Youll Do
Design and develop scalable, high-performance backend services and APIs.
Implement integrations with AI platforms and services.
Work with AI specialists to translate AI capabilities into production-ready features.
Ensure high reliability, performance, and security of AI-powered systems.
Collaborate with product and engineering teams to gather requirements and deliver solutions.

At our company, we aren't building a single, generic chatbot. We are building a Composable AI Microservice Architecture, a swarm of hundreds of hyper-specialized AI services, each meticulously "programmed" to solve small, focused tasks with high precision. This fleet powers Ava, our AI support engine, and a suite of cutting-edge generative tools for travel and expense management.
As a Senior AI Ops / MLOps Engineer, you are the architect of the platform that makes this scale possible. You will move beyond traditional MLOps to manage a "factory" of Language Models. Your challenge is one of orchestration and standardization, ensuring that every service in the swarm meets a rigorous bar for quality, reliability, and cost-efficiency.
What You'll Do
Orchestrate the AI Fleet: Build and own the runtime environment for 100+ specialized AI services. Manage model routing, context versioning, and standardized memory/history stores.
High-Density Inference Optimization: Design and implement SageMaker Multi-Model Endpoints (MME) and Inference Components to serve multiple tuned SLMs per GPU, maximizing hardware utilization while minimizing latency.
Deterministic Service Excellence: Treat reliability as a layered engineering problem. Build deterministic "shells" around probabilistic LM outputs, prioritizing data-layer validation and strict serialization.
Automated Evaluation & Observability: Implement "LLM-as-a-judge" patterns and automated benchmarking to detect semantic drift and hallucinations across the fleet before they impact the user.
Standardize the Workflow: Obsess over building reusable patterns and Terraform-based infrastructure that eliminate "snowflake" configurations, allowing us to deploy new specialized AI tasks in minutes.
Agency Strategy: Partner with AI Researchers to find the "Goldilocks zone" for agentic autonomy-balancing the flexibility of LLM tool-use with the precision required for production stability.

The Vision
We believe that Software Engineering is the highest-leverage human workflow in the company. In an AI-native world, the bottleneck is no longer how fast we can type, but how quickly we can validate, iterate, and deploy. Engineering excellence is our ultimate competitive advantage. As a Senior Software Engineer for AI Assisted Engineering Support, you will build the "intelligence layer" for our development teams. You aren't just building tools; you are building agents that understand our codebase, our standards, and our intent. Your goal is to move the company toward a "Demo to Prod" reality where AI handles the boilerplate, the testing, and the initial PR generation, leaving humans to focus on architecture and high-level logic.
The Mission: Agentic Engineering
Consistent with our "Human Centric Workflows" philosophy, you will treat LLMs as programmable functions grounded in our specific codebase. You will build the specialized assistants that integrate into our IDEs and CI/CD pipelines to unblock developers, automate reviews, and ensure that "gold-standard" code is the default, not the exception.
What Youll Do:
Build AI Engineering Assistants: Develop and scale the internal agents that assist with code generation, automated refactoring, and documentation.
Enable the "Demo to Prod" Pipeline: Work on the technical implementation of tools that allow for one-shot workflows-moving from a prototype or a spec directly to a production-ready Pull Request.
Deterministic Engineering Evals: Drive quality by prioritizing determinism. You will build the serialization formats and retrieval systems (RAG) that give engineering agents the exact context they need from our repositories to be precise and useful.
Automated Code Stewardship: Create agents that help maintain our "Immune System"-automated drift detection, visual regression testing, and security scanning for AI-assisted contributions.
Systemic Optimization: Implement a culture of rigour. You will run experiments across different models and tools, using engineering-specific benchmarks to ensure our assistants are actually increasing velocity and quality.
Global Collaboration: Partner with the US and Israel-based teams to integrate your assistants into our global developer platform and telemetry frameworks.