Senior AI Platform Engineer – Production & LLM Workflows

Cloudbeds; San Diego (CA); On-site; USD 160,000 - 250,000; Full time

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 seeking an experienced software engineer to design, build, and operate customer-facing AI platform services, including agent runtimes, workflow orchestration, tool execution, and evaluation capabilities. You will lead technical initiatives to improve reliability, observability, scalability, latency, and cost, while collaborating across product and engineering teams.

The role requires strong production Python skills and hands-on experience with agentic systems or LLM-powered

Qualifications

• > Requires 5+ years of experience building and operating production software systems.
• > Strong production Python skills.
• > Hands-on experience with agentic systems or LLM-powered workflows.
• > Experience with distributed systems, APIs, testing, cloud infrastructure, and AI evaluation or observability.
• > Ability to collaborate across a polyglot stack and communicate in business-level English.

Responsibilities

• > Design, build, and operate customer-facing AI platform services and features, including agent runtimes, workflow orchestration, tool execution, and evaluation capabilities.
• > Improve the reliability, quality, observability, scalability, latency, and cost of production AI systems while providing technical leadership and collaborating across product and engineering teams.

Skills

Python

Agentic Systems

LLM Workflows

LangChain

LangSmith

LangGraph

MCP

Vector Databases

Retrieval-Augmented Generation

AI Evaluation

PHP

Java

PostgreSQL

SQS

gRPC

REST APIs

Tools

REST APIs

gRPC

SQS

PostgreSQL

Job description

Cloudbeds is seeking an experienced software engineer to design, build, and operate customer-facing AI platform services, including agent runtimes, workflow orchestration, tool execution, and evaluation capabilities. You will lead technical initiatives to improve reliability, observability, scalability, latency, and cost, while collaborating across product and engineering teams.

The role requires strong production Python skills and hands-on experience with agentic systems or LLM-powered