Senior AI Platform Engineer: LLM Workflows & Observability

Cloudbeds

Las Vegas (NV)

On-site

USD 140,000 - 210,000

Full time

3 days ago
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Benefits offered by this job

Paid Time Off
Fully Paid Parental Leave
Home Office Stipend
Professional Development Courses
Manager Training
Upskilling
Knowledge Transfer

Job summary

Cloudbeds is looking for an experienced engineer to build and operate customer-facing AI platform services and product features in Las Vegas. You will implement agentic systems and LLM-powered workflows, focusing on scaling, reliability, and observability across a polyglot stack.

You will collaborate with product, design, data, security, and engineering teams to ensure robust performance and quality feedback loops.

Qualifications

  • 5+ years of experience building and operating production systems.
  • Strong production Python skills.
  • Hands-on experience with agentic systems or LLM-powered workflows.
  • Experience with AI frameworks and evaluation or observability.
  • Distributed systems and APIs.
  • Cloud infrastructure and containers.
  • Testing.
  • Collaboration across a polyglot stack.

Responsibilities

  • Build and operate customer-facing AI platform services and product features.
  • Establish model evaluation, tracing, observability, and quality feedback loops.
  • Collaborate across product, design, data, security, and engineering teams.

Skills

Python
Agentic Systems
LLM Workflows
LangChain
LangSmith
LangGraph
MCP
Retrieval-Augmented Generation
Vector Databases
AI Evaluation
LLM Observability
PHP
Java
PostgreSQL
AWS
Docker

Tools

LangChain
LangSmith
LangGraph

Job description

Cloudbeds is looking for an experienced engineer to build and operate customer-facing AI platform services and product features in Las Vegas. You will implement agentic systems and LLM-powered workflows, focusing on scaling, reliability, and observability across a polyglot stack.

You will collaborate with product, design, data, security, and engineering teams to ensure robust performance and quality feedback loops.

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