לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 189 משרות

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.

Palo Alto Networks is seeking a Senior or Principal Backend Engineer (we are open to hire both levels) for our Cortex engineering group, focusing on Cortex XSOAR, Cortex XSIAM, and new Cortex AI solutions. In this role, you will design and implement robust backend services for our leading-edge security orchestration, automation, and response platform. You will also contribute to creating innovative AI-based solutions, enhancing shared Cortex infrastructures. This is an exceptional opportunity for those eager to advance Cortex products with AI-driven capabilities and make a significant impact in the cybersecurity industry.
Your Impact:
Own the end-to-end backend development of features and components, from design and development to testing, deployment, and maintenance.
Proactively collaborate and exchange information with peers across different teams and disciplines to shape solutions and ensure alignment on product integrations.
Contribute to team-wide efforts including code reviews, design reviews, and architectural decisions, ensuring high-quality and maintainable code.
Apply a production-oriented approach, providing real-time mitigation and effective solutions to production issues to ensure platform stability and reliability.
Challenge curiously and positively by exploring new technologies and methodologies to enhance our backend services and AI capabilities.

Required Principal AI Software Engineer (CORA AI)
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 CyberArks 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.

We are looking for a highly motivated AI Research Student for our Robotics & Simulation AI team. You will be passionate about data science, AI quality measurement, and the intersection of AI with high-accuracy industrial domains. This role is ideal for someone who grows with challenging existing assumptions, defining rigorous evaluation methodologies, and pushing AI systems toward measurable reliability. You will combine strong data science and research skills with hands-on experimentation in a production AI product that controls robotic manufacturing simulations.

Key Responsibilities

AI Quality & Stability Research

Define and implement metrics to measure the stability, accuracy, and reliability of our production AI Copilot (PSCoPilot)
Design evaluation frameworks for AI agents operating in safety-critical robotics and simulation environments
Build observability and tracing pipelines using platforms like Langfuse to monitor Copilot performance, token usage, latency, and tool-calling success rates
Analyze failure modes, hallucination patterns, and tool-calling accuracy across 48+ MCP-exposed robotic operations
Develop automated regression and benchmark pipelines to track Copilot quality over time

Data Science & Experimentation

Conduct statistical analysis on Copilot interactions (tool selection accuracy, collision detection correctness, path planning success rates)
Research and apply techniques from AI evaluation literature (LLM-as-judge, human-in-the-loop validation, domain-specific benchmarks)
Leverage LangChain and similar orchestration frameworks to prototype evaluation chains, structured agent workflows, and comparison experiments
Explore how multi-layer agent architectures (fast triage + deep execution) affect accuracy and cost trade-offs
Challenge the team with data-driven insights on where the Copilot underperforms and why

Domain AI Research

Investigate how to improve AI reasoning for robotics tasks requiring high precision (welding, clearance checking, reachability analysis)
Research grounding techniques that reduce errors in domains with zero tolerance for incorrect outputs
Explore and apply new AI technologies (GenAI tools, AI coding assistants, agents, MCP-based solutions) to enhance Copilot capabilities
Validate technical feasibility through hands-on experimentation with our production MCP bridge and two-layer streaming agent engine

Communication & Documentation

Document findings, benchmarks, and technical recommendations
Present results to technical and business partners
Collaborate with the team to translate research insights into production improvements