Logz.io is hiring a

GenAI Software Tech Lead

Tel Aviv-Yafo, Israel
Full-Time
At Logz.io, we are at the forefront of automating observability, pushing the boundaries of cloud observability with AI and cutting-edge technologies. We are integrating Generative AI into our platform to further our journey toward autonomous observability.


About the Position

  • At Logz.io, we are focused on advancing key observability metrics, with a particular emphasis on MTTR (mean time to recovery). We are seeking a GenAI Software Tech Leader who will design and build scalable AI solutions. We are looking for someone who enjoys exploring uncharted territories, has the ability to read and interpret scientific papers and other relevant materials, and is unafraid to experiment in both research and development.

Responsibilities

  • Lead the design and implementation of generative AI solutions for observability use cases such as log summarization, root cause analysis, and alert generation.
  • Continuously research emerging AI technologies and techniques to enhance our platform.
  • Architect scalable infrastructure to support AI-driven features across the Logz.io platform.
  • Collaborate with cross-functional teams to define and execute the AI strategy.
  • Promote AI best practices, including model performance evaluation, data privacy, and responsible AI deployment5+ years in software engineering, focusing on AI/ML or data-intensive systems.

Requirements

  • 5+ years in software engineering, focusing on AI/ML or data-intensive systems.
  • Experience with LLMs, orchestration frameworks, RAG, and AI agents. 
  • Proficiency in Python and strong understanding of prompting best practices for LLMs.
  • Creative problem-solving, a "can-do" attitude, and a hacker mindset.
  • Ability to communicate complex AI concepts to both technical and non-technical stakeholders.

Advantages

  • Experience with LangChain, LlamaIndex, OpenAI, AWS Lambdas, and AWS Bedrock.
  • Familiarity with observability products and telemetry data (logs, traces, metrics).
  • Knowledge of MLOps, large-scale data pipelines, NLP, and conversational AI.

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