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Llm Knowledge Graph Jobs in Oregon (NOW HIRING)

Convert your own resolution work into reusable automation, playbooks, and knowledge that agentic ... Demonstrated experience building or tuning automation or agentic and LLM-based support tooling, or ...

Implement LLM-based systems with: * Tool-calling frameworks * Retrieval-Augmented Generation (RAG ... Knowledge of: * Signal processing or physics-based modeling * Graph-based reasoning or causal ...

LLM-based applications, Agentic AI workflows, AI copilots and automation solutions, knowledge ... Lang Chain, Lang Graph' Llama Index, Semantic Kernel, OpenAI frameworks * Strong programming ...

Knowledge of web security, GitOps, and Kubernetes customization. * Basic understanding of AI/ML ... Hands-on experience building and deploying GenAI/LLM-powered solutions in client or production ...

Llm Knowledge Graph information

What is the difference between Llm Knowledge Graph vs Data Scientist?

AspectLlm Knowledge GraphData Scientist
Required CredentialsKnowledge of NLP, graph databases, machine learningStatistics, programming, data analysis
Work EnvironmentResearch labs, AI companies, tech firmsCorporate, consulting, research institutions
Industry UsageAI, knowledge management, semantic webBusiness analytics, predictive modeling

While both roles involve data and machine learning, Llm Knowledge Graph specialists focus on building interconnected knowledge bases using NLP and graph technologies, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap in AI projects but serve different core functions within organizations.

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Senior Support Engineer

Obsidian Security

OR • On-site, Remote

Other

Posted 15 days ago


Job description

Senior Support Engineer

Team: Global Services & Delivery Location: [Remote / Hybrid - specify] Reports to: Head of Customer Support

About the role

Obsidian Security protects organizations against threats across their SaaS and identity environments. This role sits at the technical center of how we deliver support. It has two mandates. First, you own our hardest problems: complex, high-severity, and escalated tickets that require deep technical diagnosis. Second, you help build the systems that will let us scale support through technology rather than headcount, partnering directly with the Head of Customer Support to design and operationalize our agentic support capability.

This is a hands-on individual contributor role for someone who is equally comfortable resolving the toughest customer issue in the queue and turning that resolution into automation that prevents the next one.

What you'll do
  • Own complex, high-severity, and escalated tickets end to end, acting as the top technical escalation point before engineering.
  • Diagnose deep technical issues across APIs, identity and authentication, integrations, telemetry, and product data flows.
  • Partner with the Head of Customer Support to design, build, and continuously tune agentic support systems, including automated triage, resolution, and knowledge retrieval.
  • Convert your own resolution work into reusable automation, playbooks, and knowledge that agentic systems can execute without human involvement.
  • Identify where automation and agentic resolution fail, then close those gaps to raise deflection and automated resolution quality.
  • Interface with Product and Engineering on root cause analysis, bug escalation, and permanent product fixes.
  • Set the technical quality bar for the support function and mentor other engineers on it.
What we're looking for
  • A strong hands-on technical support or support engineering background for a technical B2B SaaS product. Cybersecurity, identity, or SaaS security context is strongly preferred.
  • Depth across APIs, authentication and identity, logs and telemetry, integrations, and systematic debugging.
  • Demonstrated experience building or tuning automation or agentic and LLM-based support tooling, or clear aptitude and appetite for doing so.
  • The ability to translate messy, one-off escalations into repeatable, automatable solutions.
  • Comfort operating with ambiguity in a function that is being actively rebuilt around technology.
Nice to have
  • Scripting or coding ability, for example Python, and comfort debugging at the API level.
  • Experience with LLM and agent frameworks, retrieval-augmented generation, or workflow automation.
  • Familiarity with identity provider and SaaS administrative APIs, such as Microsoft Graph and Entra, or comparable platforms relevant to SaaS security.