לוח משרות דרושים הייטק AI , לחיפוש זה נמצאו 313 משרות

We are seeking a Senior AI Engineer to join 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 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.
The 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.

we are a rapidly growing, award-winning B2B tech unicorn with an ambitious mission to revolutionize the payroll & payments industry. With over $400M raised from multiple tier-one investors, our innovative technology provides a comprehensive solution for managing global workforces, encompassing everything from hiring and onboarding to managing and paying employees in over 160 countries.
We're building AI to tackle one of the hardest operational challenges in business: getting workforce management right across many markets, each with its own tax rules, labor laws, payment rails, and constantly shifting policies.
In this role on our AI team, you'll focus on agentic workflow automation. You'll design, build, and deploy reliable AI agents that automate complex HR, payroll, and payment workflows, handling decision-making, document intelligence, and complex tasks that typically require human judgment.
What You'll Do
Design and build agent-based systems that automate document processing, business insights, and complex enterprise workflows
Build observability, evaluation, and feedback loops for agent behavior to improve reliability, accuracy, and trust in production
Own the technical architecture and engineering standards for agentic systems
Build or manage data pipelines to process large volumes of documents and unstructured data
Collaborate with domain experts to identify high-value automation targets and deliver end-to-end solutions
Stay current on agent frameworks, LLM capabilities and limitations, and apply emerging patterns pragmatically in production.

we are a rapidly growing, award-winning B2B tech unicorn with an ambitious mission to revolutionize the payroll & payments industry. With over $400M raised from multiple tier-one investors, our innovative technology provides a comprehensive solution for managing global workforces, encompassing everything from hiring and onboarding to managing and paying employees in over 160 countries.
We're building AI to tackle one of the hardest operational challenges in business: getting workforce management right across many markets, each with its own tax rules, labor laws, payment rails, and constantly shifting policies.
In this role on our AI team, you'll build and scale core AI systems that power our company's products. You'll work across agentic document intelligence, autonomous agents, compliance AI, and ML-powered insights, prototyping quickly, building robust evaluations, and shipping production-grade AI with real business impact.
What You'll Do
Build and ship AI/ML solutions using LLMs, agents, RAG, and document understanding models, alongside classic ML
Prototype quickly, validate feasibility, and turn strong POCs into production systems
Evaluate models and architectures, apply testing and guardrails to improve agent and service reliability
Research and apply emerging techniques: multimodal/document AI, agentic frameworks, synthetic data generation, and new architectural approaches
Work cross-functionally with product, R&D, and compliance teams to deliver end-to-end solutions
Contribute to scalable, secure architecture and engineering best practices for AI delivery.

we are looking for a Applied AI Researcher.
The Dream-Maker Responsibilities
Open Research Tracks
Familiarity with at least one is expected:
Computer Vision: object detection, segmentation, multimodal grounding, vision-language models, contrastive and self-supervised representation learning, low-resource and few-shot visual recognition.
NLP / Speech: LLMs, NERs, relation extraction, span-based and generative IE, semantic textual similarity, multilingual and cross-lingual transfer.
Reinforcement Learning: MDPs, POMDPs, model-based and model-free RL, Online Offline methods, reward modeling, sim-to-real transfer, compute-aware planning.
Graph Learning: GNNs, graph clustering, community structure, generative methods, knowledge graph embeddings, dense and sparse semantic retrieval.
Optimization: convex and nonconvex optimization, constrained and Lagrangian methods, combinatorial and integer programming, knowledge distillation (response, feature, and relation-based), test-time optimization, Bayesian optimization, resource-aware inference.
Representation Learning: contrastive learning, self-supervised and unsupervised pre-training, disentangled representations, metric learning and embedding spaces, cross-modal and multimodal alignment, meta learning (hypernetworks), transfer learning and domain adaptation, probing and interpretability of learned representations, world models.
Neurosymbolic AI: neuro-symbolic integration, differentiable theorem proving, inductive logic programming (ILP), probabilistic soft logic (PSL), causal inference and structural causal models (SCMs), programmatic and compositional reasoning
Responsibilities:
Train and evaluate models across research tracks, iterating fast while documenting rigorously.
Build and maintain benchmarking pipelines and evaluation suites.
Curate, structure, and preprocess datasets; contribute to synthetic data generation workflows.
Run ablations and controlled experiments to support research hypotheses.
Reproduce and stress-test results from recent literature relevant to the group's work.
Collaborate across tracks and with engineering teams through to production handoff.

You will join the Deployment Platform team, which puts technology directly in the hands of customers, field technicians, and partners. As an AI-Native mobile engineer, your primary development framework is Flutter (with native iOS and Android used when needed), building the mobile application central to field deployment. You are also comfortable across the full stack to ensure end-to-end feature delivery. Most importantly, you will shape the next generation of agentic installation experiences that define how industrial AI reaches the factory floor. This is a high-impact role at the intersection of mobile, IoT, and AI.
A Day In Your Life:
Design, build, and maintain high-quality, cross-platform mobile applications for iOS and Android using the core Flutter/Dart stack.
Lead the design and shipment of agentic-first workflows for guided installation, leveraging LLMs (Azure OpenAI, Gemini) to assist technicians and automate decision-making in the field.
Implement complex IoT/Hardware integration features, including NFC provisioning, AR field tools, and indoor positioning/navigation.
Contribute to backend and frontend services/APIs to ensure seamless, end-to-end feature delivery.
Architect and maintain a scalable, modular monorepo, ensuring robustness through strong state management (BLoC/RxDart) and comprehensive test coverage.
Collaborate with product and design teams to deliver exceptional UI/UX, including adaptive and RTL-aware layouts.

we are looking for a Experienced AI Software Engineer.
You are a Senior AI Software Engineer looking to join a GenAI Infrastructure team and build production-grade GenAI capabilities and the infrastructure behind them. You will be a hands-on engineer focused on AI agents, RAG pipelines, tool-calling workflows, backend services, data access layers, evaluation, observability, and reusable GenAI infrastructure used across product teams. You will not be focused solely on model research or prompt design. Instead, you will be a strong software engineer who can design, build, ship, and operate reliable AI-powered systems in production.
A Day In Your Life :
Build reusable infrastructure, SDKs, and internal frameworks for AI-powered product capabilities.
Design and implement AI agents, RAG flows, tool-calling workflows, and LLM orchestration pipelines.
Build production-grade GenAI services, APIs, and backend infrastructure.
Integrate LLM workflows with internal microservices, data platforms, vector search, and event-driven systems.
Design secure data-access patterns that enforce authorization, tenant separation, and user-level scope.
Implement evaluation, tracing, monitoring, and quality-control mechanisms for GenAI systems.
Improve latency, reliability, fallback behavior, cost efficiency, and production readiness.
Work on customer-facing AI experiences, including conversational and proactive agentic product flows.
Collaborate with backend engineers, product managers, data engineers, AI/ML engineers, and domain experts.

What You Will Do:
Research and prototype novel approaches to application security that go beyond traditional AppSec tooling.
Build proofs-of-concept for advanced prevention, detection, triage, and remediation capabilities.
Design experiments and validate new security features through data-driven testing.
Partner with product and engineering to bring successful POCs into the core platform.
Evaluate and optimize LLM-based agents and model outputs for security use cases.

DealHub.AI is building the future of agentic revenue technology. Trusted by leading global businesses, we’re redefining what revenue teams can achieve with AI and agentic execution across the deal lifecycle. Our mission is simple: help businesses Own Your Revenue with greater speed, intelligence, and governance. As an AI Solution Expert , you will serve as the technical trusted advisor for our customers, bridging AI capabilities with their specific business goals and revenue workflows. You will embed deeply with customers. Part consultant, part engineer, part strategic advisor: leading AI sessions, configuring AI-driven workflows using DealHub MCP, training users on best practices, and ensuring measurable business outcomes. You'll collaborate closely with Customer Success, Product, Support, and Engineering teams, and will be the go-to expert for any AI-related technical solution. This is an ideal role for someone who thrives at the intersection of cutting-edge AI technology and real-world business challenges. This role is ideal for someone who thrives on ambiguity, moves fast, and finds equal satisfaction in writing clean code and presenting a solution to a CFO. Key Responsibilities
* Embed deeply with customers to understand their technical environment, business processes, and AI workflows and then design and build solutions that fit.
* Build and deploy AI-powered workflows, MCP-based automations, and intelligent features within the DealHub platform tailored to each customer's use case taking into account the integration landscape such as Salesforce, HubSpot, Dynamics, NetSuite, and billing platforms.
* Leverage LLM, AI, APIs, webhooks, data pipelines, automation scripts.
* Lead technical AI sessions — review requirements, demo solutions, help build agents and perform training.
* Translate complex AI and technical concepts into clear, tangible business value; operate as a trusted advisor, not just an implementer.
* Identify and resolve technical blockers proactively; operate with confidence under ambiguity and incomplete information.
* Build reusable engineering assets: integration libraries, prompt templates, and AI workflow scaffolding that scale across the customer base.
* Act as a direct feedback loop from the field to the Product and Engineering teams surfacing patterns, edge cases, and AI feature opportunities discovered during deployments.
* Monitor post-go-live and drive continuous improvement.

We are seeking a Data Engineer with strong technical expertise and a business-oriented mindset to lead end-to-end data, automation, and AI solutions. The role requires the ability to understand business needs and translate them into scalable, reliable technology solutions.

The successful candidate will design, develop, and maintain data pipelines, automation processes, analytics, and AI-enabled solutions that drive operational efficiency and data-informed decision-making. Strong collaboration, teamwork, and communication skills are essential, including fluency in English and the ability to work effectively with both technical and business stakeholders in a local and global environment.

Experience with Microsoft technologies (e.g., Azure, Power Platform, Power BI, Copilot) is a strong advantage. The position combines hands-on data engineering with automation, analytics, and AI innovation.

we are looking for a AI-Native Pod Leader.
The AI-Native Team Leader is a new kind of engineering leader at Payoneer - equal parts technical authority, people developer, and AI-first builder. Youll lead a small AI Pod that owns its problems end-to-end: from understanding the business need, through architecture and implementation, to production monitoring. There are no hand-offs, no tickets, no specs thrown over a wall. Your team builds with AI as a primary tool, ships fast, and sets the methodology for how R&D works next.
What youll do:
Lead and develop a small 3-4 engineers AI Pod, with a clear focus on their technical growth, autonomy, and delivery outcomes
Provide technical authority hands-on - code, architect, review, and ship alongside your team
Own the full delivery loop: understand the business problem, define the solution, architect it, ship it, monitor it - no one hands you a spec
Collaborate directly with Product, Design/UX, DevOps, and business stakeholders to define decision logic, risk thresholds, and success metrics - building capabilities, not features
Drive AI-native development - Claude Code, Cursor, and whatever tools give your team the most leverage; build in a day what used to take a team a week
Build the harness before you ship - evaluation frameworks, monitoring, and observability go in on day one, not after the first incident
Be accountable for overall design, architecture, code quality, and production environment across your team
Set a higher technical bar - run design reviews, champion engineering best practices, and push for continuous improvement in code quality and team craft
Define the methodology - this is early-stage work within Payoneer; you wont inherit a playbook, youll write it

We are looking for an exceptional Principal Product Manager to help build Core AI Platform-the trusted, scalable AI operating layer enabling Product, Engineering, and Business teams to adopt AI safely and effectively.
Reporting to the Senior Product Director, Core AI Platform, you will take part in translating strategy into concrete roadmaps and capabilities, and partner deeply with Engineering, Data, Architecture, Security, and business stakeholders to deliver reusable AI capabilities across .
This role is ideal for a senior, hands-on product manager, AI savvy, who combines technical depth, exceptional product sense, execution excellence, and the ability to drive adoption across complex organizations.
What you'll do:
The Core AI Platform enables three strategic outcomes: transforming how products are built, enabling every business function to redesign and automate workflows through AI, and creating agentic customer experiences across products.
You are not building isolated AI features for one product. You are building platform capabilities, reusable patterns, and product experiences that help teams across ship trusted AI faster, safer, and at scale.
Own the roadmap for one or more Core AI Platform areas.
Translate ambiguous business and technical needs into clear requirements, milestones, and measurable outcomes.
Define and deliver scalable, secure, compliant platform capabilities across AI infrastructure, orchestration, governance, evaluation, responsible AI, APIs, and reusable services.
Partner hands-on with Engineering, Data, Security, and Architecture to make practical build, buy, partner, and integrate calls in your domain.
Lead AI-native solutions that show how the platform accelerates product development, engineering productivity, and workflow automation.
Turn early solutions into reusable patterns, templates, and components teams can adopt.
Drive and track adoption of the tools and services you will build.

The Cortex Content team powers Palo Alto Networks security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers.
We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle.
Your Impact:
Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations.
Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management.
Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes.
Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements.
Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes.

Your Career:
As a Principal AI Software Engineer on our Generative AI foundation team, you will build AI agents and shared infrastructure that power GenAI capabilities across the company. You will be involved in the full software lifecycle, from fast-moving prototypes to production-grade systems, enabling our companys product lines to adopt agentic workflows safely and at scale. You will collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence.
Your Impact:
Engage in the full software lifecycle, from fast-moving prototypes and POCs to production-grade, observable systems.
Collaborate with product managers, researchers, and engineers to translate ideas into robust services.
Work hands-on with leading LLMs and the modern agentic ecosystem, leveraging a wide range of AWS services.
Use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve solutions.
Implement solid design, flexible implementation, strong telemetry, and production feedback loops.

As a Senior Staff AI Software Engineer on our Generative AI foundation team, you will build AI agents and shared infrastructure that power GenAI capabilities across the company. You will be involved in the full software lifecycle, from fast-moving prototypes to production-grade systems, enabling our companys product lines to adopt agentic workflows safely and at scale. You will collaborate with product managers, researchers, and engineers to translate ideas into robust services, bringing a pragmatic mindset to experimentation, iteration, and operational excellence.
Your Impact:
Engage in the full software lifecycle, from fast-moving prototypes and POCs to production-grade, observable systems.
Collaborate with product managers, researchers, and engineers to translate ideas into robust services.
Work hands-on with leading LLMs and the modern agentic ecosystem, leveraging a wide range of AWS services.
Use cutting-edge frameworks and techniques to develop, evaluate, and continuously improve solutions.
Implement solid design, flexible implementation, strong telemetry, and production feedback loops.