לוח משרות דרושים AI Engineer משרה מלאה, לחיפוש זה נמצאו 140 משרות

We are seeking for a talented AI/ML developer with strong focus on Python expertise and hands-on experience in AI/ML models to join our Data Science group. The Data Science group plays a pivotal role in driving the execution and delivery of advanced AI and modern Machine Learning solutions, that empower impactful projects to our target sectors.
Key Responsibilities:
Take part in all development aspects, from concept to production, of AI/ML models and LLM-based features (agents development)
Stay up to date with state-of-the-art research in the field of LLM and apply relevant advancements to improve our solutions
Mentor new team members and share your expertise to strengthen the teams collective knowledge

We are seeking an experienced Generative AI Engineer to join our AI squad at our company. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field.
Key Responsibilities
GenAI Development & Implementation
End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities
Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations
Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python
Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services
Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions
System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability
Continuous Learning & Innovation
Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge
Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment.

Were looking for a hands-on Senior AI Engineer to both build and guide. Youll architect and ship production GenAI systems while mentoring engineers - keeping one hand on the keyboard and one eye on the roadmap. This isnt a seat at a whiteboard - its a role for someone who can write a RAG pipeline in the morning and run a technical design review in the afternoon.Youll work on client-facing projects, building AI systems that go live across organizations and industries.
What Youll Do
Lead the design and delivery of end-to-end GenAI systems - from prototype to production
Write production-quality code, review PRs, and set a high engineering bar
Build and deploy LLM-powered applications (RAG pipelines, agents, fine-tuned models)
Define architecture patterns for prompt engineering, retrieval pipelines, and model evaluation
Partner with product, data, and platform teams to deliver real-world AI solutions
Mentor engineers, contribute to design reviews, and provide technical guidance
Evaluate and introduce new tools, models, and frameworks.

We're looking for a Software Engineer with strong backend and cloud expertise to join our AI team. You'll design and build backend systems that integrate Generative AI capabilities, contributing across the stack from API development to cloud deployment.
This role is ideal for someone who thinks in systems, loves solving complex problems, and can go deep into implementation details while keeping the big picture in mind. You'll work closely with our team lead on architectural decisions and take ownership of project delivery.
Key Responsibilities
Systems Design & Development
Design and build complete backend systems APIs, databases, queues, authentication, and integrations
Develop Python services with strong focus on code quality, performance, and reliability
Design solutions that scale across different client environments (cloud and on-prem)
AI Integration
Integrate LLMs (Multi Agents Systems) and GenAI capabilities into production systems
Build orchestration layers and workflows that combine AI with traditional backend logic
Optimize AI system performance, cost, and reliability
Cloud & Infrastructure
Deploy and manage systems across major cloud platforms (GCP, Azure, AWS)
Work with cloud-native services, databases, and infrastructure tools
work with production systems, monitoring, and operational health
Collaboration & Delivery
Communicate with client development teams, DevOps, and business stakeholders
Guide frontend developers on API contracts and integration requirements
Contribute to technical decisions and solution design within the team
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance.

At UVeye, we’re on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we have pioneered the world’s first fully automated suite of vehicle inspection systems, with advanced AI at the core, spanning machine learning, GenAI, and computer vision across the automotive sector. With close to $400M in funding and strategic partnerships with industry giants such as Amazon, General Motors, Volvo, and CarMax, UVeye stands at the forefront of automotive technological advancement. Our growing global team of over 300 employees is united around a culture of innovation, excellence, and teamwork as we build a safer automotive world.
We are looking for an experienced Robotics AI Engineer to build the AI core of UVeye’s robotics inspection platform. You will design and ship the perception and policy models that let a mobile, dexterous robot approach a vehicle, position sensors, and complete inspection tasks reliably in real-world environments.
A day in the life and how you’ll make an impact
* Design and train deep learning models for robot perception, including 3D scene understanding, vehicle pose, and occlusion handling.
* Develop visuomotor and policy models for sensor positioning, navigation, and manipulation around vehicles.
* Adapt and integrate UVeye’s existing inspection models onto the robotic platform.
* Build sim-to-real pipelines and run experiments in simulation and on real hardware, iterating fast on failure modes.
* Own the technical quality and reliability of the AI stack as it moves from prototype to production.

You don't need a traditional technology background to succeed here. What we're looking for is someone who is genuinely passionate about AI, technically sharp, and capable of owning complex projects end to end. The technology operations side of the role is learnable; the drive, curiosity, and communication skills are not.
You'll be the person who shapes how our company uses AI internally, builds the systems that keep our technology running smoothly, and ensures our security and compliance obligations are met on time.
Responsibilities
Gen-AI & Intelligent Tools
You'll own this from day one. we are actively building AI into how every team operates, and you'll be the person making that happen.
Continuously explore the generative AI landscape and bring forward clear, well-reasoned recommendations on what our company should adopt
Lead the full lifecycle of AI tool rollouts, from identifying the right solution, building the business case, managing the rollout, and driving adoption across teams
Build and automate workflows using AI and no-code/low-code tools that remove friction and free up people to focus on higher-value work
Become the internal go-to for anything AI related, running training sessions, writing guides, and helping teams get practical results from the tools they use
Track and report on the ROI and adoption of deployed tools, and adjust course when something isn't working
Stay obsessively current on what's happening in AI, new models, new agent frameworks, new use cases, and translate that knowledge into concrete action
Technology Operations
Take ownership of our company's internal technology stack, including devices, software, user accounts, and day-to-day support
Manage employee onboarding and offboarding from a technology perspective
Keep SaaS tools, licenses, and vendor relationships organized and up to date
Maintain clear documentation so nothing lives only in your head
Security & Compliance
Keep ISO certification requirements on track by managing audit schedules, documentation, and coordinating evidence collection across departments
Drive SOC 2 readiness by maintaining the evidence library (access reviews, training records, change management logs) and supporting auditor visits
Vet new suppliers before onboarding by collecting security documentation, ensuring agreements are signed, and keeping the vendor register current.

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.

Were looking for a hands-on, entrepreneurial Team Lead to take full ownership of Ollys knowledge systems and build one of the most critical pillars of the product.

Responsibilities

Technical and managerial leadership of the Knowledge team
Designing and building production-grade knowledge systems at scale
Making architectural decisions and tradeoffs
(LLMs vs embeddings vs heuristics, online vs offline computation, cost vs latency)
Driving research, experimentation, and innovation around what knowledge means for AI Agents
Hiring, interviewing, mentoring, and growing the team
Working closely with Agent, Platform, and Product teams

Alice’s Innovation team builds adversarial RL environments that train the world’s most advanced AI models to be safer. Our customers are the leading frontier AI labs, who use these environments for post-training reinforcement learning and safety evaluation. This is the bleeding edge of AI safety technology: the environments you build will directly shape how next-generation models learn to resist adversarial attacks. We’re looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines. This is a builder role. You’ll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. You’ll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements. Why this role This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. You’ll be at the center of advancing AI safety, building systems that the world’s top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. There’s no playbook. You’ll write it. What you’ll do: Platform & performance
* Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
* Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
* Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
* Implement deterministic verifiers that evaluate agent behavior with zero ambiguity Customer delivery
* Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
* Translate customer specs into working environments, iterating rapidly on feedback
* Own the technical relationship: SLAs, API contracts, integration architecture
* Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
* Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces) Rapid prototyping
* Take ambiguous problem descriptions and produce working prototypes within days, not weeks
* Validate new environment types, interaction patterns, and verifier approaches quickly
* Build internal tooling that accelerates scenario authoring and testing

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

As an AI Productivity & Implementation Specialist, you will partner with business units across our company to identify where AI can eliminate friction, accelerate processes, and create measurable efficiency gains. You will not just recommend. You will build, deploy, and own the solutions end to end.
This is a high-visibility role in a team that reports to the COO. Your work will be measured in business outcomes, not activity.
What You Will Do
Partner with business unit leads and department heads to map their end-to-end processes, identify inefficiencies, and assess whether a process should be eliminated, redesigned, or enhanced with AI.
Design and deploy AI-powered automations and workflows using no-code and low-code tools (e.g. BlinkOps, n8n, Claude Cowork, GPT integrations, or similar).
Run AI productivity projects from discovery through deployment and adoption, owning the full lifecycle.
Inspect end-to-end organizational processes and evaluate whether they are needed, broken, or candidates for AI enhancement.
Translate business problems into clear AI solution briefs and present recommendations to non-technical stakeholders.
Develop organizational learning tools and lead training sessions to ensure employees actually use the AI solutions you deploy.
Track and report measurable outcomes: time saved, cost reduced, error rates reduced, cycle times improved.

Were on the lookout for a driven and experienced hands-on Engineering Team Leader to lead a group of engineers building the AI application foundation behind our next-generation cyber-AI product.
This team owns the core backend and frontend infrastructure that powers all user-facing applications - as well as the agentic and conversational frameworks that bring intelligence and automation into the experience.
As a hands-on leader, youll guide a talented team of engineers in designing and evolving the systems that enable every other Engineering group to create fast, scalable, and intelligent apps on top of our platform.
Responsibilities
Lead a multidisciplinary team responsible for backend services, frontend frameworks, and AI agent infrastructure - the technical bedrock of our product experience.
Mentor engineers, grow the team, and foster a culture of technical excellence and innovation.
Design and build robust frameworks and systems that power all customer-facing applications.
Develop the agentic and conversational architecture enabling LLM-powered user interactions and intelligent workflows.
Collaborate with AI research, data, and product teams to seamlessly integrate AI-driven capabilities into production systems.
Define and drive the technical roadmap, ensuring scalability, developer productivity, and rapid iteration.

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.