AI Automation Engineer, Finance & Operations
Build and scale AI-powered workflows across finance and operations, connecting enterprise systems through APIs and data pipelines while measuring impact and enabling teams to automate their work.
Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours
At Pavago, one of our clients is hiring an AI Automation Specialist to design, build, and maintain AI-powered automation systems that streamline operations and eliminate manual work.
This is a hands-on implementation role for someone experienced with AI integrations, workflow automation, APIs, and business process optimization. You’ll work across operations, customer support, marketing, CRM workflows, reporting, onboarding, and internal systems to build scalable automation solutions that improve efficiency and drive business impact.
Right after you apply, you’ll receive an email invitation from Spark Hire to record your Intro Video. It’s a short, self-recorded video that completes your application and allows hiring managers to get to know you before the interview process begins.
Rather than repeating your background during multiple screening calls, you’ll tell your story once, allowing future interviews to focus on meaningful conversations.
Don’t overthink it—you can record as many takes as you’d like before submitting. Your invitation will come from Spark Hire, so please check both your inbox and spam folder.
Build and scale AI-powered workflows across finance and operations, connecting enterprise systems through APIs and data pipelines while measuring impact and enabling teams to automate their work.
Design and deploy AI and Generative AI solutions, including LLM-powered applications, RAG pipelines, and agent-based automation, taking projects from rapid prototypes to production systems.
Design and own the evaluation, testing, and observability infrastructure for AI agents, building automated pipelines and statistical, regression, and adversarial tests to improve reliability, safety, and performance.
Design and own evaluation, testing, and observability infrastructure for AI agents, building automated pipelines and statistical and adversarial tests to improve reliability, safety, and performance.
Design and own the evaluation, testing, and observability infrastructure for AI agents, building automated pipelines and statistical, adversarial, and regression tests to improve reliability, safety, and performance.