LLM Observability & Evaluation Engineer

KTek Resourcing LLC

Charlotte (NC)

On-site

USD 120,000 - 180,000

Full time

2 days ago
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Job summary

KTek Resourcing LLC is seeking a GenAI / LLM Observability & Evaluation Engineer to ensure reliability and performance of production AI agents and LLM-powered apps. You will implement evaluation frameworks, tracing, telemetry, and dashboards to monitor production systems, driving incident readiness and operational excellence.

The role requires hands-on experience with LLMs, evaluation tools, Python automation, and strong observability skills to optimize performance and reliability in a

Qualifications

  • Hands-on work with LLMs, Generative AI, or Agentic AI.
  • Experience evaluating LLMs, testing agents, and analyzing performance.
  • Strong Python and test automation skills.
  • Experience with observability, tracing, telemetry and monitoring.
  • Ability to build dashboards and analyze application performance.
  • Knowledge of SLOs, production operations, incident response, and reliability.

Responsibilities

  • Implement LLM evaluation frameworks and agent testing workflows.
  • Design and operate observability, tracing, and telemetry solutions.
  • Build and maintain dashboards to monitor production AI agents.
  • Collaborate with teams to improve reliability and release quality.

Skills

LLMs / Generative AI applications
LLM evaluation & agent testing
Python programming & test automation
Observability, tracing & telemetry
Metrics dashboards & performance分析
SLOs, production ops & incident readin

Tools

OpenTelemetry
Prometheus
Grafana
Datadog
Splunk
LangSmith
Langfuse
Arize Phoenix
LangChain
Google ADK

Job description

KTek Resourcing LLC is seeking a GenAI / LLM Observability & Evaluation Engineer to ensure reliability and performance of production AI agents and LLM-powered apps. You will implement evaluation frameworks, tracing, telemetry, and dashboards to monitor production systems, driving incident readiness and operational excellence.

The role requires hands-on experience with LLMs, evaluation tools, Python automation, and strong observability skills to optimize performance and reliability in a

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