דרושים » הנדסה » AI Expert

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how evolves from AI-enhanced internal tools to customer-facing AI products.

We are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

We are hiring an AI Researcher to join the research team building the next generation of AI-native security systems. You will work alongside security and threat researchers to build large-scale AI agents that reason over software, code, endpoint activity, and security signals to detect malicious behavior, uncover vulnerabilities, assess risk, and make autonomous security decisions in real-world production environments. We are entering the Mythos era - where attackers operate at machine speed using autonomous systems and AI-generated software, and defenders must evolve the same way. We use state-of-the-art frontier models, including access to Mythos, to build reliable AI-native security systems at global scale. You will help design the evaluations, harnesses, and reliability infrastructure that make autonomous agents dependable under real customer load, while collaborating with leading AI organizations including Anthropic on initiatives such as Glasswing. This is an opportunity to work at the frontier of AI, autonomous systems, and cybersecurity while helping define how the next generation of security systems will operate.
Key Responsibilities
Build AI agents and autonomous security systems that reason over software, code, endpoint activity, MCPs, and security signals to detect malicious behavior, uncover vulnerabilities, and assess risk at production scale.
Develop systems, tooling, and infrastructure that enable agents to autonomously investigate threats, hunt for malware in massive datasets, and operate reliably in complex security environments.
Design and run experiments to evaluate frontier-model and agent capabilities in realistic adversarial scenarios, including benchmark creation, large-scale datasets, automated evaluations, and human-in-the-loop review systems.
Build the evaluation harnesses, observability systems, and reliability infrastructure required to make autonomous agents accurate, scalable, and dependable under real customer load.
Engineer for scale and performance across large distributed AI systems, including inference optimization, orchestration, batching, caching, cost controls, and graceful degradation under high demand.
Continuously evaluate emerging models, agent architectures, prompting techniques, and research directions to ensure our systems remain at the frontier of AI-native cybersecurity.
Rapidly prototype and test new approaches across reasoning, autonomy, evaluations, and security workflows as the AI landscape evolves.
Partner closely with threat and security researchers to extract domain expertise, translate analyst reasoning into AI workflows, and enable new forms of automation and autonomous investigation.
Collaborate with leading AI and security researchers to shape the future of AI-native cybersecurity as the industry transitions into the Mythos era.
Senior candidates will help define research direction, shape technical strategy, identify high-leverage problems, and influence how autonomous AI systems are deployed across the organization.

We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, youll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.

Responsibilities

Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.

Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.

Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.

Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost Can we prove it?

Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.

Partner closely with Product and engineering to focus on the customer problems with the highest security impact-and ship quickly.

We're looking for a Senior Applied AI Scientist to sit at the frontier of AI security - turning emerging threats into the detection models that protect how AI is used inside the world's largest organizations. You'll be part of the AI Security Research department, working hand-in-hand with security researchers to translate threat intelligence into trainable signals that catch malicious behavior and security risks across the AI-powered workflows of Fortune 500 companies.

You'll bring deep technical versatility - reaching for classical ML, deep learning, or agentic based approaches based on what the problem demands, and the evaluation rigor to know when a model is truly ready for the real world. If you want to define what AI security engineering looks like, not just practice it, this role is for you.

What Youll Do
Responsibilities:
Build, train, and ship detection models end-to-end, from raw data to production.
Choose the right method for each problem - traditional ML, deep learning, fine-tuned LLMs, agents or heuristics - based on theoretical insights turned into practical results.
Partner with security researchers to turn security research outputs and domain expertise into detection capabilities.
Own evaluation: design benchmarks, build labeled datasets, and define production standards.
Monitor models in production across all paradigms - ML, deep learning, LLM-based, and agentic systems to track degradation and ensure reliability
Iterate fast, with a tight feedback loop between model performance and product outcomes.

Join our AI Platform group as an AI Engineer in the AI Core team and help build the next generation of AI-powered networking and security solutions at our company.
The AI Core team is responsible for developing AI applications, intelligent agents, and backend systems that integrate directly into our company products and workflows. As part of our companys strategic AI direction, the team focuses on turning modern GenAI capabilities into scalable production systems that help customers operate, troubleshoot, investigate, and manage complex networking and cybersecurity environments more effectively.
This role combines strong software engineering, modern GenAI technologies, and deep product impact. Youll work on building production-grade AI systems, integrating LLMs and agentic workflows into large-scale products, and helping shape how AI transforms cybersecurity and networking operations across the company.
We are looking for engineers who are excited about building real-world AI systems in production, not just experimenting with models, but designing scalable applications, integrating intelligent agents into complex products, and solving challenging engineering problems with direct customer impact.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agents, and backend systems
Build intelligent workflows and agentic systems integrated into our company networking and security products
Develop scalable APIs, services, and infrastructure supporting GenAI applications in production
Integrate LLMs, RAG pipelines, vector databases, and orchestration frameworks into robust production systems
Collaborate closely with AI researchers, software engineers, infrastructure teams, and product groups to deliver end-to-end AI solutions
Improve scalability, reliability, observability, and operational excellence of AI systems
Explore and adopt modern AI engineering methodologies, frameworks, and tooling
Participate in architectural and technical decisions shaping the future of AI across our company products.

We are constantly striving to make our systems reliable, scalable, and simple to operate so our services are available to travelers when they need them most. With our continued growth, we have exciting challenges ahead and we're looking for a Senior Site Reliability Engineer to join our team in Tel Aviv. This role blends classic SRE ownership with pragmatic AI SRE work: you will build and operate the platforms, automation, observability, and incident response practices that keep Navan reliable, while helping teams use AI solutions, AI providers, and their APIs safely and dependably.



This is a hands-on engineering role, not a research role. You will partner with product, platform, data, security, support, and incident response teams to make production systems and AI-powered experiences more resilient. You will use software engineering, infrastructure as code, SLOs, telemetry, provider observability, and automation as your main tools, and you will apply AI where it creates measurable reliability value rather than novelty.



This position is based out of our new Tel Aviv office.



What You'll Do:

Support AI-based application solutions where reliability matters. Partner with the development teams building AI-powered travel experiences to support the development and production operation of their solution.
Work with AI solutions, providers, and APIs. Partner with teams integrating AI capabilities and providers, with attention to API reliability, authentication, quotas, rate limits, latency and provider-specific operational constraints.
Troubleshoot AI tools and provider issues. Diagnose failures across AI-powered workflows, provider APIs, configuration, permission errors, degraded responses and related areas.
Operate reliable production platforms. implement and run cloud infrastructure,and help product teams move quickly without compromising reliability.
Improve observability. Build dashboards, alerts, traces, logs, and runbooks that make service health clear, actionable, and tied to SLOs and customer impact.
Apply AI to SRE workflows. Prototype and productionize AI-assisted systems that create effective and efficient operations
Automate operational toil. Create tools, workflows, and automation that remove repetitive manual work and make operational knowledge easier to use.

we are a fast-growing tech company in the automotive space with hubs across the US and Israel. We are disrupting the multi-trillion-dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team at our company is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal-driven. At our core, we believe every voice has value and can impact our bottom line. We are looking for an AI AppSec Engineer to join our team and make a real impact on our Secure Software Development Lifecycle! As an AI AppSec Engineer your mission will be to be the driving force behind our secure development lifecycle. You wont just find bugs; you will help build the systems that prevent them. You will have the opportunity to help navigate the "Agentic Era" by building autonomous security guardrails, securing LLM-based workflows, and empowering developers to move fast without breaking security. You will also be responsible for working closely under the AppSec Architect. This role is based out of our Tel-Aviv site and will report to the AppSec Architect

What you will be responsible for:

* Build & automate: Develop and maintain internal security tooling, automated workflows, and AI security agents.
* Code integrity: Execute secure code reviews and provide actionable remediation guidance to engineering teams.
* Vulnerability management: Lead the tracking, triaging, and reporting of security flaws across all product lines.
* Best practice advocacy: Drive the adoption of secure coding standards, partnering with R&D and DevOps teams to embed security early and often.
* Extend our D&R capabilities: Build scalable solutions to identify malicious activity, triage alerts, and investigate and remediate incidents.
* Document: Draft requirement documents for security products and innovative technologies.
The top candidate will also have:

* Endless curiosity and passion for emerging technology
* Ability to handle prioritize and execute multiple tasks simultaneously.
* Ability to work collaboratively across multiple departments.
* Fluent in English - ability to lead meetings and present.
* Strong communication and collaboration skills.

Why you should join us:

* Our global team is made up of awesome forward thinking, innovative go-getters.
* Learning and growth opportunities within a fast-paced tech startup environment.
* Clear career advancement path for strong performers.
* We are committed to setting each other up for success. As a member of our team, you will work within an environment that encourages growth, initiative taking and continuous mutual feedback in order to reach your full potential.
* And of course, Wolt+ and lots of yummy treats in the kitchen:-) Does this sound like a perfect position for you or a friend? apply here.

We are looking for a Hands-On Agentic AI Engineer (Information Systems Team) to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.

The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end - writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.



Responsibilities:

Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations