לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 168 משרות

e are looking for a talented Cloud & AI Platform Architect.
We are looking for one architect to own both layers. Your foundation is deep platform and DevOps architecture: reliability, scalability, security, and cost efficiency of the cloud platform every R&D team builds on. Your growth edge is the AI layer: designing how agents are orchestrated, how they access tools and data safely, how we evaluate whether they work, and how we govern their cost and behavior in production.
We know agentic AI is a young discipline. We are not looking for a decade of AI experience that does not exist. We are looking for a proven platform architect who has spent the last one to two years genuinely building LLM-based and agentic systems in production, and who wants to own where this field goes inside a company that takes it seriously.

We are looking for a talented AI Solutions Engineer to join our innovative AI team. In this role, you will act as a bridge between our AI capabilities and internal customers, helping teams effectively adopt and integrate cutting-edge AI based solutions. Our team develops advanced AI applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will play a key role in ensuring these technologies deliver real value by working closely with users and contributing hands-on development. We are looking for a motivated teammate who enjoys working with technology, people and developing new capabilities.


What you'll be doing:

Lead technical engagements to showcase AI capabilities and demonstrate best practices.

Support integration of AI solutions into existing systems and workflows.

Guide users on how to effectively use AI tools and platforms to maximize impact.

Develop and customize AI solutions (e.g., RAG pipelines, LLM-based applications, evaluation, agents, etc.) based on customer use cases while ensuing high reliability.

Troubleshoot technical issues and provide hands-on support during onboarding and adoption.

We are looking for a talented AI Engineer to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes.
What Youll Do:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with engineering teams to design, build, and maintain production pipelines.

Were looking for a hands-on AI Enginee
to build and own the agentic workflows at the heart of our security intelligence engine. This is a
backend-focused engineering role
: youll design, build, and maintain the autonomous systems that execute security workflows end-to-end - taking capabilities from research prototype to scalable, production-grade infrastructure.
Youll be working at the edge of applied AI, turning LLMs and agentic frameworks into reliable, observable systems that operate in real customer environments.
What Youll Build:
Agentic Workflows (Core Focus): Design and maintain the orchestration backbone for multi-step, autonomous agents that investigate, reason about, and act on complex security operations.
Internal AI Infrastructure: Contribute to a shared platform for models, data pipelines, training, evaluation, and observability that the whole AI team builds on.
Responsibilities:
Build and maintain the agentic workflow engine - orchestration, tool use, state management, retries, and evaluation - that powers our AI-driven security features.
Develop the backend services and APIs that deploy AI capabilities safely and at scale.
Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
Own reliability, observability, and performance of the agentic systems in production.

We are seeking a talented AI Specialist in DevOPS to lead the integration of artificial intelligence (AI) and machine learning (ML) technologies into our development, research, testing, and overall software systems. The ideal candidate will possess a deep understanding of DevOPS principles, coupled with hands- on experience in implementing AI models for code generation, automation, monitoring, and other critical functions.
עוד על התפקיד
In this role, you will design and establish robust infrastructure to support multiple development teams operating across diverse domains, technologies, and environments. We expect initiative, independent problem-solving, and innovative thinking to drive AI-driven solutions that enhance our software development lifecycle.

As a Senior AI Engineer in the MSC IL AI Innovation team, you will lead the design, development, and productization of advanced AI solutions for our Specialized Clouds, with a strong focus on sovereign-first, secure, and responsible AI systems.

You will operate as a technical leader, owning end‑to‑end AI architecture and delivery, influencing platform direction, and mentoring engineers while working closely with architects, product managers, security, and operations teams. This role goes beyond implementation; you will shape how AI is built, governed, and scaled across sovereign and regulated cloud environments.


Responsibilities

Design and build AI agents that plan, use tools/APIs, manage state/memory, and reliably complete multi-step workflows.

Own AI features from design through production, including deployment, monitoring, and live‑site reliability, with an eval-first development lifecycle: define success criteria, build evaluation datasets and automated harnesses, and run human-in-the-loop reviews where needed.

Develop and maintain prompt, retrieval, and memory strategies (system prompts, few-shot examples, tool schemas, retrieval context) with proper versioning and evaluation coverage.

Debug AI behavior using prompt analysis, data inspection, and model/tool-call traces, and translate failure patterns into targeted improvements.

Establish and track AI quality metrics (e.g., accuracy, groundedness, relevance, hallucination rate) and integrate them into CI/CD release gates.

Optimize runtime performance and economics (token usage, inference cost, latency, caching, model selection/routing, batching) and implement monitoring and continuous improvement loops (online signals, drift detection, structured user feedback).

Partner with product, design, and domain stakeholders to define use cases, acceptance criteria, and rollout plans for AI features.

Live site responsibility.

we are looking for a AI Engineer.
Our R&D teams build and own the features that power platform - from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there.
What You Will Do
Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#).
Design scalable backend services that support production-grade agentic AI capabilities.
Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks.
Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production.
Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform.

we are looking for a AI Research Engineer, Security.
Our Research team operates like a startup inside : strategic, high-ownership, and working directly with leadership. We drive the innovation behind AI-native platform, researching and prototyping the next generation of capabilities and guiding both product and go-to-market teams in bringing them to customers. We work at the edge of the security industry, envisioning and building first-of-their-kind, category-defining agentic development security solutions.
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.

we are looking for a Senior Software Engineer - Integrations - AI/ML.
As a Senior Software Engineer specializing in the AI & ML ecosystem, you'll be a core contributor owning and evolving critical parts of AI ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Engineers and Data Scientists to harness speed and scale in the frameworks they already use.
We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.
You'll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation as a vector store, ML feature stores, and LLM-powered data applications.

we are looking for a AI Native Engineer (Node. js).
You will join a high-impact AI engineering team within R&D, owning problems end-to-end from understanding the business need, through architecture and implementation, to production monitoring. This is a new way of working at Payoneer: you'll work directly with business stakeholders, ship AI-driven capabilities at speed, and help define the methodology as we build it.
As a member of the AI Foundations organization, you will lead best practices, champion early adoption of new technologies, and influence the direction of our R&D guild - building and shipping cutting-edge agentic applications that deliver seamless experiences to our users.
Location
Hybrid - Herzliya, Israel
Full-time
What you'll do:
Own the full development loop understand the business problem, define the solution, architect it, build it, ship it, and monitor it in production
Use AI as your primary development tool, achieving in a day what used to take a team a week
Collaborate with your team and business stakeholders to define decision logic, risk thresholds, and success metrics
Design and build evaluation frameworks as part of every solution you don't ship what you can't measure
Own production readiness monitoring, alerting, and observability go in on day one
Contribute to shaping team practices, tooling, and engineering standards across the pod
Decompose business problems into agentic workflows, orchestrated flows, and reusable capabilities.

we are looking for a Platform Enablement & AI Engineer.
The Platform Enablement & Automation team owns configuration management across products and services, defining how they operate for different customers, partners, and markets. This scope spans pricing and fee structures, eligibility and limit policies, onboarding, and the business rules and operational controls that govern product behavior across regions.
The team functions as the rapid-delivery layer between a business requirement and a fully productized solution. When a business unit requires a new capability, a pricing change, or a configuration deployed at short notice, the team delivers it at production quality without waiting for the full product and engineering build cycle. To operate at scale, the team builds and owns its internal platform, and is progressively evolving into an AI-native, automation-first function.
This is a hands-on, individual-contributor position focused on engineering delivery and technical ownership rather than people management. The successful candidate will serve as a core builder of the platform, working across the full technology stack, from user interface through backend services to data and deployment, and will provide the technical depth and redundancy that prevents the platform from depending on any single individual.
Working in close partnership with the business teams the platform serves, the successful candidate will translate their requirements directly into working software and help extend the platform outward as it grows to support strategic partners. The role also partners with the team's Director to shape the platform roadmap and deliver against it, in daily collaboration with R&D and Product in Glilot.

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.

Are you an AI Analyst ready to translate raw model output into a reliable, high-quality production system? Do you excel at the craft of Prompt Engineering and thrive on the challenge of ensuring Generative AI output meets rigorous quality standards in mission-critical applications?
Join our R&D Operations Team. You will be the AI analyst responsible for the end-to-end quality, performance, and operational tuning of our Generative AI-driven support system (Co-Pilot). Your mission is to actively shape the model's intelligence, govern the data it uses, and implement the mechanisms that guarantee its accuracy, directly accelerating our customer support engineering velocity.
Your Impact
Support & Customer Advocacy: Champion the Support Journey in Engineering. Develop in-product support instructions that reflect and address real incoming cases, enhancing the quality and effectiveness of AI feature solutions.
Model Quality Validation: Use existing evaluation platforms and methodologies to validate production models. Monitor quality metrics to continuously assess and rank AI answers for accuracy and reliability.
Prompt Engineering & CT Loop: Drive the Continuous Training loop through systematic prompt engineering (refining and versioning inputs). Analyze failures to define R&D actions or features needed to close model performance gaps.
AI Knowledge Governance: Act as AI Content Governor, implementing controls to verify and ingest compliant knowledge base content, ensuring a quality data source.
Cross-Functional SME: Serve as the AI Support Co-pilot Subject Matter Expert, partnering with R&D and Support Enablement to translate quality issues into core model logic improvements and feature development.

Your Career:
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.

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.