Jobs
We are seeking an innovative Automation Engineer to join our Accounts Receivable Automation team at Amazon. In this role, you will leverage modern technologies including AI, Machine Learning, 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:
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Design and develop automation solutions using AI, ML, LLMs, AWS services, and RPA tools like Ui Path
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Optimize and maintain existing automations, including SQL query optimization and database management
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Partner with stakeholders to gather requirements, create technical specifications, and ensure solutions meet business objectives
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Lead multiple concurrent automation projects from inception to deployment while meeting established timelines
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Implement robust error handling, monitoring, and testing procedures to ensure automation reliability
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Coordinate with cross-functional teams to integrate solutions across various financial systems and processes
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Provide technical consultation on automation possibilities and maintain solution documentation
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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
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- Ui Path Certified Professional Developer certification
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- Experience programming with at least one software programming language, or experience in developing and deploying LLMs in production on GPUs, or other AI acceleration hardware
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- Hands-on experience with Ui Path, Automation Anywhere, or Blue Prism.
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- Experience in Python (for AI libraries) and/or C#/.NET (for RPA framework customization).
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- Experienced in consuming RESTful APIs, JSON, XML, and SQL querying.
Preferred Qualifications
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- Experience developing, deploying and managing AI products at scale
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- 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)
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- Experience using data to drive root cause elimination and process improvement
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- 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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
$1.5T
Valuation
Reviews
2.9
10 reviews
Work-life balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
Recommend to a friend
Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
4 data points
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0 reports
$108,330
total per year
Base
$43,332
Stock
$54,165
Bonus
$10,833
$75,831
$140,829
Interview experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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