We are seeking an innovative RPA Engineer to join our Accounts Receivable Automation team at Amazon. In this role, you will leverage modern technologies including AI, Large Language Models (LLMs), and traditional RPA tools to transform our financial operations.
Join our Finance Operations team to design and implement intelligent automation solutions that operate at Amazons unprecedented scale. You will work with diverse stakeholders to analyze existing processes, architect future-state solutions, and deliver high-impact automations that drive operational excellence.

Key job responsibilities

Responsibilities:

• Design and develop automation solutions using AI, LLMs, AWS services(EC2, S3 ,lambda), and RPA tools like Ui Path

• Optimize and maintain existing automations, including SQL query optimization and database management

• Partner with stakeholders to gather requirements, create technical specifications, and ensure solutions meet business objectives

• Lead multiple concurrent automation projects from inception to deployment while meeting established timelines

• Implement robust error handling, monitoring, and testing procedures to ensure automation reliability

• Coordinate with cross-functional teams to integrate solutions across various financial systems and processes

• Provide technical consultation on automation possibilities and maintain solution documentation

• Stay current with emerging technologies and contribute to the teams automation strategy through knowledge sharing and best practices

Basic Qualifications

• Ui Path Certified Professional Developer certification
• Experience programming with at least one software programming language, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
• Hands-on experience with Ui Path, Automation Anywhere, or Blue Prism.
• Experience in Python (for AI libraries) and/or C#/.NET (for RPA framework customization).
• Experienced in consuming RESTful APIs, JSON, XML, and SQL querying.

Preferred Qualifications

• Experience developing, deploying and managing AI products at scale
• Experience in creating process improvements with automation and analysis, or experience working with large-scale data mining and reporting tools (i.e. SQL, MS Power Query, Python)
• Experience using data to drive root cause elimination and process improvement
• Integrate LLMs with private enterprise data sources (PDFs, databases, internal documents) using embeddings and vector search techniques to retrieve contextually relevant information and ground AI outputs in factual data.

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