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Upwind Security
Upwind Security
51 – 200 Darbinieki
DrošībaMākoņdrošībaSaaS
Upwind Security izstrādā mākoņdrošības programmatūru organizācijām, kas izmanto vairāku mākoņu infrastruktūru. Tās platforma apvieno mākoņdrošības stāvokļa pārvaldību, izpildlaika ievainojamību pārvaldību, API drošību un citas saistītas iespējas, lai palīdzētu DevOps un drošības komandām reāllaikā atklāt apdraudējumus, noteikt ievainojamību prioritātes un efektīvāk pārvaldīt infrastruktūras un lietojumprogrammu riskus.
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Vakances uzņēmumā

AI Engineer, LLM Agents

Develop and deploy LLM agents for Upwind Security’s cloud security platform. Research, evaluate, and build autonomous workflows for investigating and remediating runtime threats.

ILIzraēlaHibrīdiPilna slodzeVidējais līmenisVecākais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta inženierisMašīnmācīšanās inženieris
AWSAzureGoogle Cloud PlatformKiberdrošībaKubernetesMākonisPython

Apraksts

  • Develop LLM agents to investigate, triage, and remediate cloud security threats.
  • Take AI work from research through production, prototyping models, techniques, and agent designs and shipping successful solutions.
  • Train, fine-tune, and evaluate security models using runtime events, cloud logs, identity data, and network activity.
  • Develop the internal AI platform, including its services, pipelines, evaluations, and observability.
  • Work with Security Researchers, Product, and Engineering to turn research into production-ready autonomous workflows.

Prasības

  • At least 3 years building production AI/ML systems, including LLM agents with modern AI and agent frameworks.
  • Strong backend engineering skills and proficiency in Python.
  • Experience training or fine-tuning machine learning models and LLMs.
  • Strong grasp of AI system reliability, including prompting and context engineering, evaluation pipelines, LLM-as-judge, regression testing, and production monitoring.
  • Demonstrated AI research skills: following relevant literature, defining open problems, designing rigorous experiments, and benchmarking techniques against current methods.
  • Ability to take ownership, work independently and collaboratively in a fast-paced setting, and connect research with product engineering.
  • Bachelor’s or master’s degree in Computer Science, Data Science, or a related discipline.
  • Preferred: Cybersecurity experience, such as cloud security, threat detection, or incident response.
  • Preferred: Practical experience with AWS, Google Cloud Platform, or Azure, and Kubernetes.
  • Preferred: Research publications, open-source contributions, or other work demonstrating AI expertise.

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