לוח משרות דרושים הייטק AI משרה מלאה, לחיפוש זה נמצאו 266 משרות

Our team is looking for a skilled professional to join the AI software group. In this role, you will focus on our AI kernel compilers, ensuring our hardware delivers peak optimization for sophisticated and custom AI kernels. You will work extensively with various kernel infrastructures, including Triton and CUDA, while collaborating closely with our AI graph compiler teams.
Responsibilities
Develop our AI kernel compilers and related components in the SW stack.
Drive the performance optimization of AI models running on our unique architecture.

Were looking for an AI Creative Gen- someone who lives and breathes visual creation and wants to redefine how video and stills are made. Think of this as the digital cinematographer of 2026. You dont just 'prompt'- you engineer multi-model workflows, integrate complex compositing techniques, and bridge disparate tools into a unified pipeline. You build, composite, and direct.
In your day-to-day, you will:
Own visual projects end-to-end - from receiving a storyboard to delivering high-end, cinematic video and stills using AI as your primary camera and studio
Direct the machine - apply your deep understanding of cinematography (lenses, lighting, camera angles, and composition) to guide AI models toward photorealistic perfection
Build & architect workflows - design and engineer hybrid production pipelines by integrating multiple models within WIVI. You will be responsible for orchestrating workflows that connect Midjourney, Image-gen models, and the latest video engines into a seamless output
Master the "non-AI" look - use VFX and compositing skills (After Effects/Premiere) to eliminate artifacts and ensure every frame feels intentional, grounded, and premium
Drive R&D through production - collaborate with the Motion Studio and Creative teams to solve high-complexity briefs. You dont innovate in a vacuum; you push the technical boundaries of AI within live projects, discovering new creative solutions and "impossible" workflows while executing at the highest level
Bridge the gap - combine AI-generated content with real-world photography or 3D renders to create seamless, high-fidelity brand stories.

We're looking for an AI Growth Marketer - someone who lives and breathes AI and wants to channel that into marketing. Think of this as the growth hacker of 2026, you're AI-native first, marketer second. AI tools are your default way of working, You build with Claude Code or OpenClaw instead of spreadsheets and slide decks. If you've ever built an AI agent for fun, automated a workflow because you were bored, or shipped a side project using vibe coding - and you're excited about applying that energy to marketing - this role is for you.
In your day-to-day, you will:
Own marketing projects end-to-end - from strategy to execution - using AI as your primary working environment, not just an assistant
Create campaigns, landing pages, product content, and customer stories at a speed and volume that would be impossible without AI fluency
Build your own tools, automations, and AI workflows to solve marketing problems
Run growth experiments across channels, rapidly testing messaging, creatives, and audiences to find what drives sign-ups and engagement
Lead product launches alongside Product and Growth teams - shaping positioning, messaging, and go-to-market plans
Stay on the bleeding edge of AI capabilities, constantly scouting new models and tools and figuring out how to apply them to marketing before anyone else does.

We are seeking a highly accomplished AI Researcher to be part of the development of next-generation Foundation Models and Generative AI systems. In this role, you will bridge the gap between cutting-edge academic research and production-grade AI infrastructure. You will build, design, and fine-tune large-scale architectures (including LLMs, Multimodal, and Tabular Foundation Models) while applying them to complex, real-world domains like agentic behavior, coding and decision making.
In your day-to-day, you will:
Conduct pioneering research in deep learning and generative AI, specializing in Foundation Models, NLP, alignment, and multimodal learning
Deal with the impact of the models on production traffic, cost quality and latency
Train and scale state-of-the-art architectures using techniques like Post-Training SFT, Knowledge Distillation, LoRA, and sparse/hybrid model architectures
Own the AI lifecycle-from algorithmic prototyping and synthetic data generation to deploying production-grade AI features in fast-paced or big-data environments
Drive research initiatives, author publications/patents, and collaborate with other research teams to integrate intelligent capabilities into core products.

This is your opportunity to get on the rocket ship and join a company that is building a cutting-edge enterprise network and secure cloud platform, and is on a fast track to becoming the worldwide market leader - dont miss it!
we are building a real-time AI runtime platform for security algorithms running inline across our global cloud and physical PoPs.
We are looking for an AI Platform Engineer to help build the infrastructure that powers high-throughput, low-latency AI security decisions in production.
You will work on a runtime engine that combines GPU-based models, from MMBERT-style models to LLMs, with CPU-based heuristics and security logic, optimized for scale, performance, reliability, and real-time execution. This is a versatile engineering role that spans AI runtime infrastructure, high-performance backend development, GPU inference, model lifecycle, and close collaboration with research teams to bring AI security algorithms into production.
Responsibilities
Build our companys AI security runtime platform for high-throughput, low-latency production serving.
Develop infrastructure for model serving, multi-model orchestration, and inline decision flows.
Optimize inference performance: batching, caching, streaming, GPU utilization, memory usage, and runtime acceleration.
Build backend orchestration and performance-critical services in Go.
Support the model lifecycle: registry integration, packaging, versioning, deployment, monitoring, and operational health.
Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.

We are looking for a Hands-On Agentic AI Engineer to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

We are looking for a Hands-On Agentic AI Engineer to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

Were looking for a hands-on Agentic AI Engineer to build practical, high-impact AI solutions that transform how our teams operate.
This is not a research role. Youll design and ship real AI systems that improve workflows across Sales, Marketing, HR, and Operations - building custom solutions where off-the-shelf tools fall short.
If you enjoy turning messy business problems into production-ready AI systems using LLMs,SLMs, agents, and smart data pipelines - this role is for you.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots) using frameworks like LangGraph / LangChain
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

we are building a real-time AI runtime platform for security algorithms running inline across our global cloud and physical PoPs.
We are looking for a hands-on AI Platform Team Lead to build and lead the team behind this platform: a high-throughput, low-latency engine that runs GPU-based models, from MMBERT-style models to LLMs, together with CPU-based heuristics and security logic.
This is a core infrastructure role for someone who wants to own the runtime layer of AI security at scale: performance, reliability, orchestration, GPU efficiency, and production-grade execution in the traffic path.
The team will also own the model lifecycle required to take AI security algorithms from research to large-scale production, working closely with research and algorithm teams.
Responsibilities
Build and lead our companys AI Platform team: hiring, mentoring, architecture, technical direction, and execution.
Own the AI security runtime platform for high-throughput, low-latency inline security decisions across our companys global cloud and PoPs.
Design the orchestration layer for running GPU models, CPU heuristics, and security logic as one production engine.
Own production readiness: observability, SLOs, autoscaling, reliability, rollout, rollback, and operational health.
Own the model lifecycle platform: registry, versioning, deployment, monitoring, and safe production rollout.
Work closely with research and algorithm teams to productionize AI security models and algorithms at scale.
Define the long-term platform strategy for AI runtime and model serving at our company.

We are looking for a Hands-On Team Lead - Agentic Engineering to lead, build, and actively contribute to a new team focused on applying AI agents, and intelligent workflows to improve business processes across the organization.
This role is both a technical leadership role and a hands-on engineering role. The successful candidate will manage the first Agentic Engineer, help grow the team, and personally contribute to the design, development, integration, and deployment of agentic AI solutions.
The ideal candidate is someone who can lead from the front: writing code, designing architectures, building prototypes, reviewing technical work, solving complex implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI-driven solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.

we are building the future of AI Security - a platform that enables organizations to adopt AI boldly while keeping it governed, observable, and secure.
Were looking for a hands-on Software Engineering Team Lead to own our AI Security product for coding agents - from Claude Code, Codex, and GitHub Copilot to cloud-native coding environments and fully autonomous development agents.
This is a high-impact, product-driven leadership role at the intersection of AI, developer experience, cloud infrastructure, and enterprise security. Youll lead a full-stack team that owns this domain end-to-end: from infrastructure and policy engines to delightful product experiences that engineering teams actually love using.
What Youll Do
Lead and grow a full-stack engineering team dedicated to securing AI coding agents and autonomous development workflows.
Own the entire product area - strategy, architecture, roadmap execution, quality, customer adoption, and continuous iteration.
Design and build production-grade capabilities spanning AWS & Kubernetes infrastructure, backend services, real-time policy & enforcement engines, rich APIs/integrations, and intuitive UI/UX.
Partner closely with Product, Design, Sales Engineering, and customers to stay ahead of emerging AI risks and developer needs.
Set a high bar for engineering quality, ownership mindset, fast delivery, and product thinking across the team.
Help shape how the industry solves one of the biggest challenges of our time: letting AI agents move at incredible speed without compromising security or governance.

The Field AI Engineering team is a unique group of professionals combining strong technical expertise, rooted in a software engineering background, with excellent customer-facing skills.
In this role, you will lead major customer engagements, both remotely and on-site, and tackle the most complex challenges faced by our customers. Some of these challenges will be addressed in-house by designing and developing tailored solutions for customer environments. Others will require close collaboration with our R&D and Product teams to deliver scalable and impactful solutions.
This position is ideal for someone who enjoys solving hard technical problems while working directly with customers and influencing product direction.
Responsibilities
Drive AI Security deal success by handling complex technical sales engagements.
Lead and participate in customer meetings, including technical deep dives, solution design sessions, and executive-level discussions, both remotely and on-site.
Collaborate closely with cross-functional teams, including Sales, Product, R&D, Marketing, Customer Success, and Professional Services, to deliver end-to-end customer solutions.
Design and develop custom features, integrations, and tailored solutions to address customer-specific environments and challenges.
Lead and support complex customer deployments, from initial design through implementation and validation.
Act as a hands-on technical expert throughout the customer lifecycle, contributing wherever needed to ensure successful outcomes.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

we are looking for a Senior AI Software Engineer to join our Generative AI foundation team. We build AI agents and shared infrastructure that power GenAI capabilities across the company, enabling CyberArks product lines to adopt agentic workflows safely, reliably, and at scale. In this role, youll be involved in the full software lifecycle - from fast-moving prototypes and POCs to production-grade, observable systems. Youll collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence. Youll work hands-on with leading LLMs and the modern agentic ecosystem, leveraging a wide range of AWS services. Youll use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve our solutions through solid design, flexible implementation, strong telemetry and evaluation, and production feedback loops.
Your Impact:
Design, develop, and deploy scalable AI agents and shared infrastructure for GenAI capabilities.
Manage the full software development lifecycle, from prototyping to production-grade, observable systems.
Collaborate with product managers, researchers, and engineers to translate ideas into robust and scalable services.
Work hands-on with large language models (LLMs), agentic frameworks, and a broad range of AWS services.
Implement strong telemetry, evaluation metrics, and feedback loops to continuously improve AI solutions.
Champion operational excellence through pragmatic experimentation, iteration, and solid design.

We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today.
Key Responsibilities:
Develop internal AI-powered products and tools used by teams across to work faster and smarter.
Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams.
Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows.
Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development.
Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption.
Work hands-on with the most advanced AI development tools and shape how the company uses them.