AI Engineer

Upwind Security

. Build LLM-based agents that investigate, triage, and remediate cloud security threats.

Posted 10/11/2026full-timeTel Aviv • IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying LLM-based agents for cloud security, with strong backend engineering skills in Python and experience in training and fine-tuning ML models. Proven ability to collaborate across teams and translate research into production-grade solutions while ensuring AI system reliability.

Highest-signal resume keywords

LLM-Based Agent DevelopmentPython ProficiencyAI System ReliabilityCloud Security KnowledgeAI/ML Production Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI/ML Systems DevelopmentModel Training and Fine-TuningContext EngineeringEvaluation PipelinesRegression Testing

Soft Skills

Strong OwnershipTeam CollaborationIndependent Work

Tools & Technologies

AWSGCPAzureKubernetes

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Data Science

Industry Keywords

Cloud SecurityThreat DetectionIncident ResponseAI ResearchOpen-Source Contributions

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityGoogle Cloud PlatformKubernetesPython

About the role

Key responsibilities & impact

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 runtime events, cloud logs, identity, and network activity.
Build and extend the internal AI platform, including services, pipelines, evaluations, and observability.
Collaborate with Security Researchers, Product, and Engineering to turn research findings into production-grade autonomous workflows.

Requirements

What you’ll need

3+ years building AI/ML systems in production, including LLM-based agents built with modern AI and agent frameworks.
Strong backend engineering skills and proficiency in Python.
Experience training or fine-tuning ML models and LLMs.
Strong understanding of AI system reliability: prompting and context engineering, evaluation pipelines, LLM-as-judge, regression testing, and production monitoring.
Proven AI research ability: track the literature, frame open problems, design rigorous experiments, and benchmark new techniques against the state of the art.
Strong ownership and the ability to work both independently and as part of a team in a fast-paced environment, bridging research and product engineering.
Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
Nice to have: Background in cybersecurity (e.g., cloud security, threat detection, incident response).
Nice to have: Hands-on experience with cloud platforms (AWS, GCP, Azure) and Kubernetes.
Nice to have: Research publications, open-source contributions, or other work that shows depth in AI.