לוח משרות דרושים הייטק AI משרה מלאה

We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.

looking for an R&D Operations Manager to be the operational backbone of our Product and Engineering organization. You'll own how we plan, build, and ship designing processes, leading strategic projects, driving automations and AI-powered workflows, and ensuring every team is aligned and moving fast. You'll be the connective glue across Product, Engineering, Design, CS, and GTM - the person who creates order from chaos and measurably increases our velocity.

Responsibilities

Lead Strategic Projects & Planning Own quarterly planning cycles, roadmap governance, and the most critical cross-functional initiatives end-to-end. Ensure 100% traceability between business goals and what we build. You don't just facilitate - you drive outcomes.
Increase Product & Dev Velocity Design and enforce processes that make squads ship faster. Identify bottlenecks, streamline workflows, and measure the impact. If it slows us down, you fix it.
Jira Governance & Dev KPIs Full ownership of Jira - boards, workflows, automations, hygiene, and reporting across all squads. Build and maintain dashboards for velocity, cycle time, throughput, and release predictability. You're self-sufficient - no engineering help needed.
Automations & AI-Powered Workflows Automate manual toil across the product org. Operationalize AI tool adoption. Eliminate repetitive work so PMs and engineers focus on high-value output, not process overhead.
Cross-Functional Alignment & Enablement Be the connective tissue between Product, Engineering, Design, Data, CS, GTM (including PMM, Professional Services, and Pricing), and Finance. Own release coordination and CS enablement - zero surprise launches, ever.
Tooling, Analytics & Knowledge Management Own the product tool stack (Jira, PostHog, Notion, AI tools) and the budget for product tools and operations - drive ROI through smart vendor selection and consolidation. Ensure PMs have self-serve access to data. Maintain a centralized knowledge base as the single source of truth.

we are looking for a AI Security Engineer.
As AI capabilities accelerate across the bank, we need an engineer to design and enforce safe AI usage-protecting customer data, preserving model integrity, and meeting our regulatory obligations. You'll be the architect of guardrails, tooling, and policies that make AI both secure and useful for product and internal teams. This isn't about slowing things down; it's about building the trust layer that lets innovation move fast without breaking things.
What Youll Actually Be Doing:
Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
Implement data minimization controls for GenAI/RAG workloads: context filtering, least‐privileged retrieval, document-level ACL enforcement, vector store hardening, and secure token/secret handling.
Threat model AI systems (apps, agents, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/jailbreaks/data exfiltration) and build mitigations.
Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive-data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
Evaluate third‑party AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
Partner across Security, Data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
Lead/participate in AI red‑teaming: automated jailbreak/prompt‑injection tests, safety benchmarks, purple‑team exercises, and response playbooks for AI incidents.
Enable the org with concise guidelines, examples, and training on safe AI development and usage.

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.

Were looking for a talented AI research team lead for the Data Science group, to help us develop advanced AI solutions that will empower impactful projects across. The Data Science group leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product, optimize processes, and deliver personalized experiences.
Lead a team of AI researchers
Manage and conduct advanced hands-on research projects that will impact 250M+ users
Leverage the latest advancements in LLM customization, multimodal models, knowledge representation, and conversational AI
Build horizontal AI capabilities to be used across
Collaborate with other internal departments to drive impactful data-driven projects.

Required Product Manager - Harmony
Job Description
As a Product Manager, you will:
Own end-to-end product strategy and execution from ideation to production and iteration
Define and evolve the hybrid AI & manual creation experience
Lead discovery processes, including market research, BI analysis, user interviews, and experimentation.
Work closely with AI teams to define intelligent behaviors, agent workflows, and system logic
Collaborate with UX, Engineering, Data, and Marketing to bring impactful features to market
Continuously analyze user behavior and feedback to refine and polish the product
Play a central role in shaping the roadmap of Harmony.

We are building a new software engineering team with strong applied AI orientation to amplify success. The team will be focusing on creating company-wide applications to address our colleagues every day problems. You will have a chance to work with a broad range of teams , helping them to be more productive with custom solutions.
Collaborate with cross-functional distributed teams.
Gather, analyze and spec out requirements, and manage product deliverables.
Design and build scalable AI-driven products addressing real-world problems.
Stay current with the latest technical advancements, particularly in the field of AI and LLMs.

Our CTO group is looking for an outstanding physical-ai applied researcher to join our team.
the CTO group is a small, elite research unit shaping the next generation of algorithmic foundations behind our autonomous driving systems. the group operates at the core of the decision-making and planning stack, addressing some of the most challenging problems in real-world autonomy. we are seeking a researcher who thrives at the intersection of Machine Learning, decision-making, and algorithmic rigor - someone who is excited about advancing learning-based approaches for safety-critical, large-scale physical systems. in this role, you will develop novel approaches for planning and decision-making in interactive, multi-agent driving environments. you will combine deep & reinforcement learning with classical algorithmic structure and formal reasoning. the problems are open-ended, scientifically challenging, and deployed at unprecedented scale. this is a rare opportunity to conduct high-impact applied research, taking ideas from theory and papers into real-world autonomous systems at scale. if youre excited about pushing the boundaries of learning-based decision-making, wed love you to join us and help shape the future of physical ai.
what will your job look like:
design and develop novel learning-based algorithms for decision-making and planning in complex physical environments.
advance model architectures for long-horizon reasoning, multi-agent interaction, and uncertainty-aware prediction.
integrate deep learning components into structured planning pipelines with clear formal objectives and safety constraints.
formulate problems mathematically and derive principled learning objectives grounded in real-world system requirements.
lead research directions from conception to full-scale production.
develop using Python (pytorch or similar frameworks) as well as C ++/gpu/cuda.

we are looking for an experienced deep learning algorithm researcher with a strong focus on reinforcement learning to join the CTO group.
our CTO group is a small, elite research and development group responsible for shaping the next generation of algorithmic solutions powering our autonomous driving systems, crowd-sourced hd maps, and advanced driver-assistance technologies. the role focuses on building a learning-based planning system that has never been deployed at this scale before, leveraging reinforcement learning to address complex, interactive driving scenarios. you will work on policy decision making that provides a holistic, system -level view of autonomous behavior, while tackling a deeply challenging technological problem- taking ideas from research to real vehicles, developing algorithms, retraining models, validating results, and seeing the impact on the road within short development cycles. this is a unique opportunity to take part in early-stage, high-impact projects, develop proof-of-concepts using cutting-edge technologies, and influence our long-term technological direction. what will your job look like:
develop and optimize reinforcement learning-based planning algorithms, including network architectures, reward design, and training processes.
apply rl to complex, interactive driving scenarios, complementing classical planning where deterministic approaches fall short.
work with large-scale simulation environments to enable learning through interaction and diverse policy behaviors.
prototype algorithms in Python and migrate performance-critical components to efficient C ++ / gpu-accelerated implementations.
take part in fast, iterative development cycles, collaborating closely with the CTO and the team to validate ideas and demonstrate working solutions.

we are now looking for a tensorrt-llm software development engineer! our company is hiring software engineers for its tensorrt-llm team. academic and commercial groups around the world are using gpus to power a revolution in deep learning-powered ai, enabling breakthroughs in areas like llm, chatgpt and generative ai that have put DL at the iPhone moment for ai. join the team which is building the inferencing software which is foundational to product lines within our company and across the industry! the ability to work on a fast-paced delivery-focused team is required and excellent interpersonal skills are a must.
what you'll be doing:
craft and develop robust inference software that can be scaled to multiple platforms for functionality and performance
performance analysis, optimization, and tuning for large language models (llms)
conduct unit tests and performance tests for different stages of the inference pipeline.
closely follow academic developments in the field of artificial intelligence and feature update tensorrt-llm
write safe, scalable, modular, and high-quality ( C ++/ Python ) code for our core backend software for llm inference.
collaborate across the company to guide the direction of deep learning inference, working with software, research and product teams

in this role, you will manage a team of ai/ ml engineers, lead the innovation and development the different solutions, and collaborate with cross-company teams. we are looking for an experienced, hard working manager who can collaborate effectively and has a deep technical capabilities in both ai/ml and software development.
what you'll be doing:
manage a team of 6-8 engineers
formalize the team work methodologies, collaboration, etc.
provide technical leadership, mentorship, and guidance to foster team growth.
supervise and build ai best in class solutions, including data ingestion, rag, mcps, agents, self service, and more.
be a part of an experienced team with a great atmosphere.
collaborate with cross-functional teams to identify and implement ai opportunities

we are in search of a top-tier ai agents solution architect to work closely with hardware architects, Verification engineers, gpu performance experts, and software developers to develop end-to-end agent flows that drive significant enhancements in simulation analysis, Kernel optimization, and Developer efficiency.
what you'll be doing:
develop innovative ai flows to improve hardware and software through collaboration with various engineering roles.
facilitate co-creation workshops to transform sme rules of thumb into specific assignments, resources, cues, and guidelines. define success measures, evaluation data, and feedback loops for agents to make a measurable difference in nvidia's hw simulation analysis and gpu- Kernel optimization workflows.
rapidly prototype and thoughtfully productize; integrate with internal services, utilize gpu capabilities, remove bottlenecks, and deliver fitting solutions.
set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements.
mentor and improve teams through insights in agent orchestration, prompting, rag, observability, crafting documentation and playbooks for teams.

you will work at the intersection of Machine Learning and software engineering - selecting the right models, feedback strategies, and evaluation frameworks to make ai-generated code reliable, high-quality, and trustworthy.
what you'll be doing:
design and build ai-powered development pipelines - from code generation and automated review to feedback loops and evaluation systems.
evaluate and select ml approaches for specific problems: when to use llm prompting vs. fine-tuning (qlora), classical ml (random forest, linear regression) vs. reinforcement learning, rag vs. structured extraction.
architect feedback and evaluation systems that measure and improve ai output quality over time.
review and refine ai solution architectures - evaluate design decisions, identify weaknesses, propose alternatives with reasoning.
lead proof-of-concept development to validate new ai/ml approaches for development tooling.
collaborate with the core team to define risk-based development levels and calibrate ai review depth per level.

our company has been transforming computer graphics, pc gaming, and accelerated computing for more than 25 years. its a unique legacy of innovation thats fueled by great technology-and amazing people.
today, were tapping into the unlimited potential of ai to define the next era of computing. an era in which our gpu acts as the brains of computers, robots, and self-driving cars that can understand the world. doing whats never been done before takes vision, innovation, and the worlds best talent. as an our employee, youll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. come join the team that is building ai platform for operating ai factories to make a lasting impact on resilient operations of ai clusters.
what will you be doing:
you will bring together and understand internal and external customer requirements to improve ai cluster resiliency and design aiops-based solutions that address these needs.
develop automated workflows for issue detection and root cause analysis and closely collaborate with operators to debug sophisticated, Full-Stack ai cluster problems. we will bring to bear the findings for product improvements!
deliver compelling technical presentations and lead hands-on demos or training. you'll also handle evaluation deployments (poc/pov) and ensure smooth, reliable installations by staying engaged and encouraging throughout the customer journey.

the road algorithm team is responsible for one of the most critical and challenging tasks in autonomous driving - detecting and understanding the drivable road. our work leverages deep neural networks and geometric modeling to deliver reliable and high-quality road perception for autonomous vehicles. we are looking for an expert deep learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities. what will your job look like:
conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
lead exploratory investigations into new architectures, training strategies, and data utilization methods
join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
own projects end-to-end - from concept and experimentation to integration and scalable deployment