AI-Driven Enterprise Integrations Engineer

Cloudflare; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Cloudflare, Austin-based, is seeking an engineer to design and maintain AI-assisted integration workflows between Cloudflare and a variety of SaaS applications. You’ll evaluate where an LLM, agent, or automation layer can replace brittle logic, speed up development, and improve operational response.

You will build and extend internal AI tooling and collaborate with stakeholders to translate business problems into technical solutions, while growing into larger initiatives and end-to-end projects.

Qualifications

• Bachelor's degree in Computer Science or related field (or equivalent work experience).
• 3+ years of professional software engineering experience.
• Proficiency in at least one backend language (Go strongly preferred; Python/TypeScript also considered).
• Experience using AI/LLM tools to build real solutions (AI agents, automation, or AI-assisted development).
• Experience building RESTful APIs with proper service security practices.

Responsibilities

• Design and maintain integration workflows between Cloudflare and SaaS applications.
• Evaluate AI/LLM-based approaches to improve design, speed, or operations.
• Build and extend internal AI tooling (agents, skills, automation scripts).
• Collaborate with stakeholders to translate business problems into technical solutions.
• Contribute to governance of AI tooling, data handling, and guardrails.
• Lead larger initiatives and own end-to-end integration/UI/MCP projects as you grow.

Skills

Go

Python

TypeScript

LLM tooling

REST APIs

CI/CD

Kubernetes

Observability

Education

Bachelor's degree in Computer Science or related field

Tools

Grafana

Prometheus

Sentry

Kibana

GitLab

Cloudflare Workers

Job description

Cloudflare, Austin-based, is seeking an engineer to design and maintain AI-assisted integration workflows between Cloudflare and a variety of SaaS applications. You’ll evaluate where an LLM, agent, or automation layer can replace brittle logic, speed up development, and improve operational response.

You will build and extend internal AI tooling and collaborate with stakeholders to translate business problems into technical solutions, while growing into larger initiatives and end-to-end projects.