לוח משרות דרושים AI Engineer בתל אביב יפו, לחיפוש זה נמצאו 74 משרות

We are seeking a Senior AI Engineer to join our companys core product organization, where you will design, build, and scale next-generation AI systems powering real-world cybersecurity use cases across our diverse product portfolio (Posture, Detection, and CTI). This role focuses on developing production-grade systems leveraging LLMs, advanced machine learning, and agent-based architectures.
You will join a team within our companys Cyber R&D organization-leading the companys core product portfolio- while driving AI innovation and establishing engineering best practices across the domain. The team focuses on building and optimizing large-scale AI systems, including LLM-based solutions and advanced multi-agent workflows, working closely with data scientists and researchers to bring ideas into production.
Responsibilities
Design, build, and own end-to-end AI solutions- from data collection and preprocessing to model training, evaluation, and production deployment.
Optimize systems for performance, scalability, and reliability in production environments.
Collaborate closely with product, design, and engineering teams to identify and deliver AI-driven capabilities that address real customer needs.
Stay up to date with emerging AI/ML technologies, frameworks, and best practices, and apply them where they create real impact.
Work across the stack, contributing to backend systems and data pipelines that support large-scale AI applications.
Troubleshoot and resolve complex system issues, including performance bottlenecks, race conditions, and memory-related challenges.
Approach problems with a strong analytical mindset, delivering robust solutions while contributing to a high-performing, collaborative team environment.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Design and build complex, interactive UIs with React, TypeScript, and Next.js.
Apply design engineering principles to translate Figma designs into highly polished, responsive implementations.
Own component architecture: build reusable, composable, and well-documented components.
Own production health and observability to ensure system reliability at scale.
Ensure accessibility and cross-browser compatibility.
Write tests and maintain code quality across the frontend codebase.
Collaborate with design, backend, and product teams to ship features end-to-end.
Mentor engineers and promote frontend engineering best practices.
Leverage Al-assisted development tools to accelerate workflows and improve code quality.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Design and build agentic systems - single and multi-agent workflows with planning, memory, context engineering, and tool use - for both internal automation and product-facing autonomous capabilities operating over long time horizons.
Build and operate the AI platform layer - LLM gateways, prompt management, structured output handling, tool-calling infrastructure, and cost/latency optimization - deployed on Kubernetes, consumed by every team for their agentic work.
Own the agent framework layer - orchestration primitives, execution environments, state management, and sandboxed tool execution - giving every team at our company the building blocks to create and operate their own agents.
Build evaluation infrastructure that gives teams confidence in agent behavior - automated LLM and agent evals for quality, correctness, safety, latency, cost, and regressions, including human-in-the-loop oversight for mission-critical workflows.
Productionize and harden backend services (APIs, gRPC, async workers) that integrate LLMs - with proper error handling, retries, circuit breakers, and high-availability patterns.
Own RAG pipelines and retrieval systems - indexing, chunking, embedding, vector database management, filtering, and relevance tuning for production retrieval.
Optimize performance and cost across the AI stack - model routing, caching, batching, and inference cost management.
Ship shared tooling - libraries, SDKs, agent templates, and documentation - while working closely with ML Platform, Data Platform, DevOps, and other teams across the Applied AI Engineering group. Own architecture, documentation, and operations end-to-end.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Built as part of a broader sovereign AI platform, our technology is designed to operate in on-premise, private cloud, and air-gapped environments, enabling nations to maintain full control over their data, infrastructure, and AI capabilities. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
Responsibilities
Build and operate ML training infrastructure - distributed training pipelines, compute scheduling, and reproducible experiment workflows that data scientists rely on daily.
Own model serving and inference systems - packaging, deployment, autoscaling, A/B testing, canary rollouts, and latency/cost optimization for production models.
Run feature stores, model registries, and dataset versioning - enabling self-serve feature engineering, model lineage, and reproducible experiments across teams.
Build experiment tracking and evaluation infrastructure - automated evals, comparison dashboards, drift detection, and monitoring that give teams visibility into model behavior and performance.
Build and maintain production pipelines for training, fine-tuning workflows, and serving domain models - owning reliability, reproducibility, and scale.
Build and maintain the monitoring and observability layer - model performance tracking, data and prediction drift detection, data quality validation, and alerting.
Improve performance and cost across the ML stack - training throughput, inference latency, batch vs. real-time tradeoffs, and compute cost management.
Ship shared tooling - libraries, templates, CI/CD for models, IaC, and runbooks - while collaborating across Data Platform, AI, Data Science, Engineering, and DevOps. Own architecture, documentation, and operations end-to-end.

We are looking for an AI-first Software Engineer who is highly product-oriented and excited about building customer-facing systems using modern AI tooling to dramatically increase development speed and operational automation.
What youll do?
Build and ship end-to-end product features (backend, frontend, integrations, automation).
Use AI tools and build the AI infrastructure to accelerate development through scalable workflows, including multi-agent approaches.
Build AI agents that fully automate customer-facing sales and service flows, in a business with a massive volume of textual interactions.

Required Al Infrastructure & Reliability Engineer
What this role is really about
Youll join a 3-person platform team within our Business Technology group -owning the internal infrastructure that our AI platform and its users depend on. This isnt a product engineering role, and it isnt ticket work or babysitting pipelines someone else built. Youre building and operating the internal foundation that the company runs on. The work covers the full stack of platform engineering: core cloud infrastructure (AWS, Kubernetes, IaC), CI/CD pipelines, AI-driven infrastructure components, and the SRE and observability practice that keeps it all honest -metrics, alerting, incident response, and reliability standards. As our AI capabilities grow, so does the complexity underneath them, and staying ahead of that is central to the role. If you treat infrastructure as a product -reusable, automated, observable, and built to last -this is your kind of role.
Job responsibilities
DevOps & AI-Driven Infrastructure - own CI/CD, deployment processes, and release reliability. Build and operate cloud infrastructure that is automated, intelligent, and continuously self-improving - not just managed.
Design and build our Terraform repository and IaC pipeline from scratch -AI-assisted generation, drift detection, and policy enforcement built in.
Build AI-driven GitHub Actions pipelines -automated code review, risk assessment, and intelligent deployment decisions.
Manage Kubernetes workloads across AWS accounts -zero downtime, fully automated, nothing left behind.
Embed AI into the operational layer -proactive drift detection, automated remediation, and intelligent scaling toward a self-healing runtime.
Reliability & SRE -improve uptime, resilience, and incident response.
Define and enforce SLOs/SLIs, error budgets, and on-call practices.
Lead incident response, postmortems, and systemic reliability improvements.
Own AI-specific reliability: model latency SLOs, token quota monitoring, rate limit handling, fallback and retry strategies, and cost-per-request alerting.
Observability & Telemetry - increase visibility, reduce noise, improve troubleshooting.
Establish and continuously evolve the observability stack: metrics, logs, distributed tracing, and alerting tuned for both application and AI workloads.
AI / LLM Operations- bringing AI systems to production and operating them at scale, with a focus on reliability, performance, and trust.
Own the AI infrastructure layer: rate limits, quota management, latency SLOs, and fallback strategies (retries, circuit breakers).
Operate LLM APIs in production with resilience and cost attribution per team/model.

we are looking for a AI Backend Engineer.
As the AI Backend engineer , you will join a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll utilize technical skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Design, develop, and maintain backend services for AI agents and tool integrations using latest technologies
Build scalable APIs and microservices that interface with LLMs and AI frameworks
Implement agent orchestration systems, tool calling mechanisms, and workflow engines
Optimize performance and reliability of AI-powered applications at scale
Develop data pipelines for training, evaluation, and monitoring of AI systems
Integrate with various LLM providers (OpenAI, Anthropic, etc.) and manage API interactions

Lead the team building the agentic infrastructure powering Klaudia - our AI SRE. You'll own the architecture, set the technical direction, and push experimental ideas into production.

This isn't a coordination role. You'll be a technical leader who builds alongside your team - setting the bar for architecture quality, driving experimental bets, and turning research into production-grade systems.



What will you do?

Own the agentic infrastructure- You're responsible for the architecture of Klaudia's core - the systems that make autonomous investigation, root cause analysis, and self-healing possible at scale.

Build and grow your team- Hire great engineers, mentor them, run meaningful design reviews, and build a culture of high ownership and engineering excellence.

Drive experimental development- Run structured bets - LLM evaluation frameworks, new agent architectures, novel tool-use patterns - and bring the best ones to production.

Stay hands-on You'll design systems, review PRs critically, and write code where it matters. Your technical credibility is the foundation of your leadership.

Shape our AI strategy- Work closely with product and R&D leadership to define what Klaudia becomes next.



Why this role rocks?

Category-defining work- AI SRE is the hottest space in cloud infra. You'll be leading the team that defines what it means - not catching up to anyone.

Real autonomy- You'll set the technical roadmap for Core. No pre-solved problems handed down to you - you decide what gets built and how.

Build something that lasts- Hire and shape a team from an early stage. Your engineering culture decisions here will compound for years.

Serious engineering culture- High bar for craft, strong team around you, and leadership that respects technical depth over process theater.

Build the future of AI in the world of Cloud Infrastructure. You'll design innovative solutions powered by AI and help shape where we're headed as a company.

Why This Role Rocks:

Develop cutting-edge AI solutions - We're harnessing LLMs to solve real cloud infra problems, not just for buzzword points
We build the future - AI SRE became the hottest market in the cloud infra space - its our job to lead it.
Your ideas become reality - Propose solutions, lead initiatives, and see your impact
Shape our tech direction - You'll have a real voice in our technical strategy.
FULL Ownership: We believe in taking developments end to end. From ideation all the way to production.

We're looking for a technical Product Manager to join AI product team and own the roadmap for Klaudia - our autonomous AI SRE agent. You'll work directly with customers, solution architects and R&D leads to define how Klaudia senses, investigates, decides, acts, and validates across availability issues and reliability risks. It's a role for someone who can translate complex AI/infra tradeoffs into a sharp product strategy.

What you will do

Work on the product roadmap execution, aligned with mission and customer needs
Collaborate with engineering and design teams to drive AI to success
Conduct thorough market research, close work with sales teams and customer calls to identify trends, customer pain points, and opportunities for AI integrations
Effectively communicate product vision, progress, and outcomes to internal stakeholders and customers
Define KPIs around AI capabilities and utilize data-driven insights to make decisions and product iterations

We are looking for a hands-on GTM AI Engineer to design, build, and deploy AI-powered workflows and automations across our go-to-market (GTM) systems.
This role sits at the intersection of business operations and technology, and acts as the engine behind revenue intelligence, process automation, and scalable pipeline generation systems.
You will be a technical force multiplier for our GTM team including creating workflows, agents, and integrations, embedded directly into core business systems (e.g., CRM, marketing automation, support tools).
This is not a traditional software engineering role, but it requires strong technical execution and ownership across the full lifecycle.
What youll do:
Design, build, and maintain production-grade AI workflows and automations to streamline GTM execution (e.g., lead enrichment, routing, research, follow-ups, CRM hygiene, and customer handoffs)
Develop and deploy LLM-based solutions, including prompt-driven workflows, reusable prompt libraries, and AI agents embedded within business systems
Build and maintain integrations and data pipelines across CRM, marketing automation, enrichment tools, and internal systems to ensure reliable, connected data across the funnel
Own workflow performance, review success metrics, iterate and demonstrate business impact.
Build and maintain AI-assisted pipeline inspection tools to give RevOps and Sales Leadership real-time visibility into deal health
Identify opportunities to reduce manual work and improve efficiency across RevOps, Sales, Marketing, and Customer-facing teams
Partner with cross-functional stakeholders to map processes, identify bottlenecks, and prioritize high-impact automation opportunities
Drive adoption through enablement: documentation, training, and ongoing feedback loops
Evaluate and implement new tools and technologies based on ROI, scalability, and maintainability

Were looking for a seasoned R&D Team Leader to join our top-notch technology R&D team, reporting directly to the VP R&D. In this role, you will drive technological innovation, oversee the development of cutting-edge features, and guide the team in delivering scalable, high-quality products. You will combine hands-on technical leadership with strategic oversight, ensuring that our platform continues to evolve and deliver impactful solutions for our clients. As part of an AI-first company, our web team is deeply involved in creating and integrating AI-driven features to enhance our digital offerings.



Key Responsibilities:

Lead the R&D team in developing new features and enhancing our platform.
Oversee the end-to-end development lifecycle, from ideation to deployment.
Ensure high-quality code, scalable architecture, and smooth product delivery by implementing best practices in software development.
Mentor and support team members in their professional growth.
Troubleshoot and resolve complex technical challenges in collaboration with the team.
Collaborate with cross-functional teams including Product, Data, and AI to align development efforts with company goals.
Drive innovation and stay updated on new technologies to keep us at the forefront of the industry.

Were looking for a Software Engineer - Data Operations Platform to join our Data Operations team and help build the internal systems and platforms that power our data workflows at scale.

This is a unique opportunity for an early-career engineer who enjoys solving practical problems, building impactful tools, and working closely with data, AI, and operations teams. In this role, youll design and develop scalable internal platforms, automation systems, and AI-driven workflows that support large-scale data operations, including tooling for computer vision workflows, automated QA systems, taxonomy management, and database navigation tools used daily across the company.

As part of a fast-moving startup and an industry leader in AI-driven creative analytics, your work will have a direct impact on engineering efficiency, workflow automation, system scalability, and data quality.



Key Responsibilities

Design, develop, and maintain internal tools and systems that support Data Operations workflows.
Build scalable automation systems for QA processes, taxonomy applications, and large-scale data handling.
Collaborate closely with Data, AI, Product, and Operations teams to solve practical business and operational challenges.
Write clean, maintainable, and reliable code with a strong focus on usability, scalability, and efficiency.
Improve internal workflows by identifying bottlenecks and building scalable solutions.
Work with databases and data pipelines to support operational and analytical needs.
Troubleshoot issues, optimize existing tools, and continuously improve system reliability and performance.
Contribute ideas, experiment with new technologies, and help improve developer workflows and internal processes.

we are looking for a AI Adoption Engineer.
Responsibilities
1. Use Case Discovery & Prioritization
Embed with non-R&D teams (CS, Sales, Marketing, Finance, HR, Operations) to understand workflows and identify where AI creates the highest leverage.
Define and prioritize whats worth building, maintaining a live backlog aligned with VP of AI.
Good discovery is the difference between automation that gets used and automation that gets ignored.
2. AI Tool Development & Delivery (~40%)
Build custom tools, workflow automations, Cowork skills, and AI integrations with existing business systems.
Validate with real users, iterate on adoption signals, and transition stable tools to team ownership.
This role leads by shipping. Working tools - not proposals - are the primary output.
3. Enablement & Adoption
Ensure tools get used: onboarding sessions, playbooks, and hands-on support through behavior change.
Build team confidence and self-sufficiency over time; avoid creating dependency on a single person.
4. AI Landscape Awareness
Evaluate new models, tools, and capabilities for internal relevance and bring what matters back to .
Collaborate with VP of AI to maintain a current roadmap for internal AI operations.