דרושים » AI » AI Engineer

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 an AI Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
Youll design, build, and ship the AI systems behind Alex: production agents that reason over customer identity data, call real tools, and complete IAM tasks end to end. Starting from a cybersecurity need, youll frame the technical problem, choose an approach, and own the solution through production: architecture, implementation, evaluation, deployment, and iteration on real customer behavior.
Youll build on our companys shared agent infrastructure and extend it: new tools and integrations, workflow orchestration, context and memory management, evaluation harnesses, and the guardrails that keep an autonomous agent safe inside a customers environment.
This is a hands-on engineering role, not a research position. The goal is not to prove that an idea can work; it is to make it useful, reliable, and observable for customers in production.
What You'll Do:
Design, implement, and ship AI-powered features for complex cybersecurity workflows, from prototype to production.
Build the systems that make agents work in practice: tool integrations, planning and orchestration logic, context management, structured outputs, and recovery from failures.
Choose the right technical approach for each problem, combining models, deterministic logic, data, and conventional software where appropriate.
Define quality for each use case and build the evaluation pipelines that measure correctness, task completion, consistency, safety, latency, and cost, and wire them into CI and release.
Debug agent behavior in production: trace failures to their root cause in the prompt, tool, data, or architecture, and fix it.
Own the reliability, observability, and cost of the agent systems you build.
Collaborate with cybersecurity experts, product, and platform engineers throughout development.

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.

We're looking for an AI Researcher to help design and enhance core intelligence capabilities. You'll work at the frontier of large language models and conversational AI - run experiments, develop novel techniques, and transform research breakthroughs directly into product impact. This is a role for someone who wants to research real-world challenges and ship to production: you'll be pushing the state of the art in domains like conversational dynamics, speech understanding, and agentic question answering, while seeing your work reach millions of language learners.
What You'll Do:
Drive original AI research across LLMs, dialogue systems, speech, and language understanding - from hypothesis through design and all the way to deployment
Design and run rigorous experiments; develop novel model architectures, fine-tuning strategies, and training methodologies
Own the full research lifecycle - ideation, experimentation, evaluation, and deployment into production
Apply and extend state-of-the-art techniques (RL, instruction tuning, RAG, agentic workflows, multimodal models) to real user-facing challenges
Collaborate with engineering and product to transform research findings into shipped features
Define research direction in your area and contribute to long-term AI roadmap

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 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 are seeking an innovative AI Engineer to join our team in building the next generation of security protection and cyber attack detection for endpoints. In this role, you will leverage cutting-edge AI technologies and advanced agentic approaches to revolutionize how cyber threats are identified, analyzed, and mitigated. You will design, build, and optimize intelligent AI agents that analyze complex security data to deliver highly accurate, automated verdict decisions on malicious activities, ensuring endpoint resilience against sophisticated attacks.
Key Responsibilities
Agentic Framework Design: Design and implement intelligent, multi-agent AI systems capable of executing complex security analysis workflows and automated decision-making.
Context Optimization: Analyze diverse security datasets to determine the most effective context, telemetry data, and threat intelligence to feed into AI agents to maximize decision accuracy and minimize false positives.
Model Configuration & Integration: Evaluate, configure, and deploy a variety of state-of-the-art language models and AI architectures tailored for high-performance security use cases.
Data Analysis & Performance Evaluation: Perform deep data analysis on security events and model outputs to continuously refine agent logic, benchmark performance, and optimize AI-driven detection mechanisms.
Collaboration & Deployment: Partner with security research and engineering teams to integrate intelligent AI components into production systems seamlessly and securely.

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.

A Senior AI/ML Engineer role on our Data team, sitting at the intersection of AI engineering, data science, and data platform. You'll build agentic, LLM-based systems that turn vast amounts of unstructured information into high-quality structured signals - powering our products and surfacing legal risk - owning each solution across the full lifecycle, from exploration to production. You'll work closely with data engineers, data scientists, product managers, and legal experts to turn ambiguous problems into scalable AI capabilities. This is a hands-on role for someone with strong engineering judgment, deep data/ML expertise, and a focus on reliability beyond the prototype stage.

What You'll Do

Design, build, deploy, and operate production AI systems: agentic, LLM-based extraction workflows and batch/online inference pipelines and owning them from exploration through deployment, monitoring, and iteration.
Define quality metrics and build evaluation datasets, testing processes, and feedback loops for ML and LLM systems; monitor accuracy, latency, cost, and data quality, and investigate and fix failures.
Explore large, complex datasets to surface useful features and patterns, and translate findings into production-grade implementations.
Partner with data engineers on ingestion, transformation, orchestration, and storage to deliver dependable data products.
Use AI-assisted coding tools (e.g., Claude) effectively while maintaining strong technical judgment and ownership of your systems.
Help shape engineering standards for production AI: testing, observability, reproducibility, data lineage, versioning, and safe deployment.

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.