AI Automation Engineer V

New

AvalaraEnterprise automation

Listing locations: USA; offering a fully remote work arrangement.Full-TimeSenior

Salary126,000 - 244,000 USD per year

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Job Details

Experience: 10+ years of experience in enterprise automation, workflow engineering, integration engineering, or platform architecture
Required Skills: AWSGCPOAuthAzureCI/CDRESTful APIs

Bachelor's degree in computer science, engineering, or a related field.
10+ years of experience in enterprise automation, workflow engineering, integration engineering, or platform architecture.
Deep hands-on experience with n8n or Boomi, including designing and operating enterprise automation solutions and AI-enabled workflows.
Expertise in API-first and event-driven architectures, REST APIs, webhooks, OAuth, JWT, and secure integration practices.
Experience implementing CI/CD, automation governance, observability, and reliability practices across enterprise-scale platforms.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience with AI and machine learning services and large language model integrations.
Ability to identify high-value AI automation opportunities and build AI-enabled solutions responsibly.
Ability to measure business impact, influence technical direction, and raise engineering standards through mentorship and leadership.

Own and help execute Avalara's enterprise AI automation and transformation strategy, with n8n as a core workflow orchestration platform.
Design and build scalable, secure automation solutions to reduce manual work and improve business process efficiency.
Develop AI-enabled workflows, intelligent agents, and decisioning frameworks across business functions.
Architect API-first and event-driven integrations connecting enterprise systems, automation platforms, and AI services.
Establish standards for development, deployment, monitoring, reliability, and governance across automation initiatives.
Define and maintain CI/CD processes, environment strategies, and release practices.
Create reusable automation frameworks, workflow templates, prompt patterns, and AI agent accelerators.
Implement observability, monitoring, and performance measurement for traditional and AI-driven workflows.
Lead technical design reviews, workflow assessments, and post-incident reviews.
Mentor engineers and implementation partners in AI automation, agent orchestration, responsible AI, and workflow engineering.

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