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Software Development Engineer II, FinTech Account Receivables Cash Applications

Amazon

  • Hyderabad, India
  • Competitive Package
  • 5+ Years
  • Posted Today
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About the role

Description

Are you interested in building high-performance, globally scalable Artificial Intelligence (AI) based Financial systems that support Amazon's current and future growth? Are you looking to partner with our science teams to build customized ML models and integrate with Generative AI models. Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services?

Do you have a passion for ensuring a positive customer experience? This is the job for you.

Amazon Financial Technology Team is looking for a results-oriented software development engineer, who can help us create the next generation of distributed, scalable financial systems. Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business contexts that are typically being defined in real-time. We need someone to design and develop services that facilitate global financial transactions worth billions (USD) annually.

A Software Development Engineer (SDE) at Amazon works on real world problems on a global scale, owns their systems end to end and influences the direction of our technology that impacts hundreds of millions of customers around the world. You can expect to design flexible and scalable solutions, and work on some of the most complex challenges in large-scale computing by utilizing your skills in data structures, algorithms, object oriented programming, GenAI and machine learning. Coming to Amazon gives you the opportunity to work on a small development team in one of our many rapidly growing organizations.

You will learn all about how to design, implement and test highly scalable solutions using AWS cloud platform and its many products, in challenging agile projects, working with best in class professionals.

Key job responsibilities

Build services/integration for Financial Applications using Native AWS services, machine learning and generative AI.

Design and Develop integration patterns for our system. Leverage and integrate with different tools, technologies and products within Amazon to reduce operational cost and enhance customer experience.

Partner directly with other Software Development Engineers (SDEs), Technical Program Managers, ML scientists, Product Managers, Functional Analysts and Customers to understand features and continuously identify opportunities to build and deploy software solutions.

Basic Qualifications

  • 5+ years of non-internship professional software development experience
  • 5+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • 5+ years of full stack development experience

Preferred Qualifications

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

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.

Company - Amazon Dev Center India - Hyderabad

Job ID: A10583550

Eligibility & process

Who can apply

Seniority: Mid-Senior level. Employment type: Full-time

Skills & stack

Next.js AWS Machine Learning Generative AI / LLMs Data Structures & Algorithms OOP Python/Java System Design

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Next.js, AWS, Machine Learning, Generative AI / LLMs, Data Structures & Algorithms, OOP, Python/Java, System Design) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Amazon Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Amazon as a Software Development Engineer II, FinTech Account Receivables Cash Applications?
Highlight Amazon's market reputation, recent tech innovations, and how your skills in Next.js directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Amazon Competitive Package
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