דרושים » AI » AI Engineer - next-generation Cyber security

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 are looking for a Senior Backend Engineer with a strong passion for AI and intelligent systems to join our growing R&D team.
In this role, youll be building the backend foundation that powers our AI-enhanced security analytics, autonomous detection, and real-time decisioning systems. Youll work closely with AI engineers, product, and security experts to bring agentic intelligence into our companys runtime platform - transforming how modern apps defend themselves.
Youll architect and implement services that scale to massive volumes of runtime data, integrate large language models (LLMs), and support RAG-based workflows for contextual understanding and response.
Youll Be Great For This Role If You Love To:
Design and build scalable, resilient backend services that power our companys AI-driven runtime security platform.
Integrate LLMs and agentic AI components into production environments to enable autonomous detection and remediation capabilities.
Design evaluation frameworks for measuring model performance and reliability in real-world conditions.
Develop Retrieval-Augmented Generation (RAG) pipelines tailored to application security data.
Own backend architecture decisions - from data modeling to performance optimization - across Node.js, Python, and cloud-native environments.
Contribute to our infrastructure, leveraging CI/CD, Kubernetes, Docker, and modern observability practices.
Mentor peers and help shape our companys AI engineering culture.

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

As an AI Engineer at Glow, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive Glow's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.

This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.

WHAT YOULL DO

End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.

Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.

Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.

Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.

Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

to join Research team. You'll help build our core intelligence engine: LLM agents that run cloud security workflows end to end. These agents investigate runtime detections, reason over workload, identity, and cloud context, and drive remediation in production. You'll research new models and agent designs, run rigorous experiments, and ship what works as high-impact features in our platform.
What you will do:
Build LLM-based agents that investigate, triage, and remediate cloud security threats.
Own the path from research to production: prototype new models, techniques, and agent designs, and ship the ones that work.
Train, fine-tune, and evaluate models for security tasks using vast data sources: runtime events, cloud logs, identity, and network activity.
Build and extend our internal AI platform: services, pipelines, evals, and observability.
Collaborate with Security Researchers, Product, and Engineering to turn research findings into production-grade autonomous workflows.

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.

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're looking for an
AI Engineering Lead
to help drive the quality, intelligence, and continuous improvement of AI and agentic systems.
This is a
hands-on AI engineering lead role focused on data, evaluation, and agentic workflows.
You'll build the systems and methodologies that allow us to understand how our agents perform, identify where they fail, and continuously improve their reasoning, tool usage, and outcomes.
You'll work closely with AI Researchers, Engineers, and Product teams to turn experiments into reliable, high-performing AI systems - from defining evaluation datasets and metrics to improving agentic workflows and deploying them at scale.

Were hiring an AI Engineer to design and build the intelligence layer behind our autonomous offensive security platform.

Youll develop AI agents capable of performing vulnerability discovery and exploitation at the level of top human white-hat hackers - combining deep security expertise with advanced AI reasoning and decision-making.

This role, reporting directly to our Agent TL, offers the opportunity to define how AI transforms offensive cybersecurity.

Youll collaborate closely with AI researchers, software engineers, and security experts to translate penetration-testing workflows into intelligent, automated capabilities - systems that plan, execute, and adapt in real time.

If youre passionate about AI, thrive in fast-paced environments, and want to shape the future of autonomous cybersecurity - wed love to meet you.

Responsibilities
Design and implement autonomous AI agents for penetration testing and vulnerability exploitation.
Translate offensive security workflows into intelligent, multi-step reasoning systems.
Develop modules for exploit generation, payload delivery, and adaptive vulnerability scanning.
Collaborate with AI researchers to fine-tune and evaluate models that enhance reasoning, adaptability, and precision.
Build evaluation frameworks to measure exploit success, learning performance, and reliability.
Ship production-ready AI systems that improve the speed, depth, and scalability of security testing.
Establish best practices for safe and controlled deployment of AI agents in offensive environments.