דרושים » הנדסה » Senior AI Engineer (Cortex XSOAR/XSIAM)

We are looking for a Senior AI Ops Engineer to join our AIOps team and help build the AI-powered platforms, agents, and workflows that enable engineering teams across our company.
This is a hands-on role for someone who can take AI solutions from idea to production, build the infrastructure around them, and create the observability needed to understand and improve how they behave in the real world.
Job responsibilities
Build and operate production-grade AI agents, AI-enabled tools, and workflows that empower developers and operational teams.
Design agentic systems using frameworks such as LangGraph, LangChain, and Supervisor, including RAG, MCP integrations, tool calling, and guardrails.
Build and evolve an AI SDLC harness that helps teams plan, implement, validate, govern, and safely deliver AI-assisted software changes.
Lead AI observability with Langfuse and OpenTelemetry, including tracing, evaluations, quality measurement, and cost analysis.
Build automated evaluation frameworks, including LLM-as-a-judge, to improve the reliability and quality of AI systems.
Design and maintain the infrastructure, CI/CD pipelines, GitOps workflows, and security controls that support AI services.
Develop internal developer tooling and automation that removes friction across the engineering organization.
Partner with engineering and product teams to turn real operational challenges into scalable AI-powered solutions.

Join our Security Autonomous SOC Team as a Principal AI Engineer to transform innovative AI/LLM research into impactful cybersecurity product features. You will leverage and augment our existing infrastructure, including BI systems and CI/CD pipelines, to design, develop, and deploy advanced LLM and Agentic capabilities. Your expertise in software development, AI engineering, and modern LLM technologies will directly drive the evolution of our security operations. By building robust, production-ready AI solutions, you will make a tangible difference in protecting our digital world against complex threats.
Key Responsibilities
Design and build Agentic security solutions to improve detection, response, and remediation capabilities.
Architect, implement, and optimize end-to-end LLM pipelines ensuring scalability from data ingestion to deployment.
Develop and deploy AI agents leveraging LLMs to automate complex security decision-making tasks.
Integrate LLM APIs and fine-tune models for specific cybersecurity use cases.
Transform promising AI and LLM research concepts into mature, robust, and scalable production-ready features.
Augment established BI data systems and CI/CD pipelines to support advanced AI development and experimentation.
Develop specialized tools and frameworks extending infrastructure to support AI-driven security research and remediation.
Collaborate with cross-functional teams to integrate AI innovations into customer-facing XDR, EDR, and SOAR platforms.

We're looking for a hands-on Agentic AI Engineer to build practical, high-impact AI solutions for our Product Support organization.
This is not a research role. You'll design and ship real AI systems that improve support workflows and processes - building custom solutions where off-the-shelf tools fall short. The role also requires close collaboration across teams: aligning with different stakeholders' needs and priorities, and building strong, ongoing partnerships across the organization.
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) using frameworks like LangGraph / LangChain
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 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.

a global technology organization developing shared platform services and enterprise applications, with a strong focus on reliability, security, and scalability, is looking for a hands-on senior software engineer with a strong focus on ai-powered development, intelligent agents, and process automation. the role combines Full-Stack engineering with building smart tools and automated workflows using technologies such as claude code, helping improve engineering productivity, streamline processes, and reduce manual work.
responsibilities:
use claude code and other ai-powered tools to accelerate coding, testing, debugging, and documentation.
build intelligent agents, internal tools, and automations to optimize workflows and reduce repetitive tasks.
identify opportunities to leverage ai to improve engineering efficiency and operational processes.
develop frontend applications using React, JavaScript, and typescript.
build backend services and rest apis using C # and.net core.
develop automated tests and end-to-end validation workflows.
automate the validation of integrations and high-volume data operations.
integrate ai-driven solutions into existing development workflows and platform services.
collaborate with a globally distributed engineering team to deliver reliable, scalable solutions.

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 our 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 our 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 we evolve from AI-enhanced internal tools to customer-facing AI products.

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.

Join our marketing engineering team and take ownership of the AI-powered systems, internal tools, and automations that multiply our team's impact.
In this role, you will bridge the gap between engineering and marketing operations by building fully autonomous agents, streaming data pipelines, and internal AI tools. Your daily work will involve identifying manual marketing workflows, designing system architectures, and shipping production-ready software end-to-end to scale our marketing infrastructure. As our AI Marketing Builder you will:
Design, build, and deploy agentic AI workflows and multi-step autonomous pipelines to automate complex marketing operations
Develop AI-powered internal tools, including content assistants and automated campaign generators, leveraging our own product ecosystem
Build and maintain scalable data pipelines pulling real-time performance analytics from various marketing channels into unified dashboard platforms
Architect end-to-end full-stack systems from scratch, choosing the optimal technical stack, APIs, databases, and server infrastructure
Collaborate directly with non-technical marketing stakeholders to translate operational challenges into clean technical solutions
Take full ownership of the product roadmap, surfacing technical blockers early and shipping high-impact software continuously
Work closely with the R&D team on marketing related feature launches.

We are seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.

Key responsibilities

Lead a team of data scientists, data engineers and product analysts

Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation

Drive excellence, code quality, and best development practices

Provide technical direction and hands-on guidance for complex AI systems

Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences

Ensure AI solutions are safe, scalable, observable, and continuously improving

Lead initiatives around product data analysis and experimentation

Analyze user interactions with product features to improve accuracy, UX, and business impact

Partner with product teams to define metrics, dashboards, and experiments that guide product improvements

Design system architectures for AI-enabled applications at scale

Evaluate and select technologies for AI platforms and data pipelines

Guide the development of prompt engineering frameworks and centralized prompt management

Ensure robust monitoring, evaluation, and feedback loops for AI outputs

Translate product and business goals into technical roadmaps and execution plans

Drive alignment between AI capabilities and measurable product outcomes

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.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
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.