Software Development Engineer, FinTech - TFAW

Amazon; Hyderabad; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Amazon Dev Center India - Hyderabad seeks a software engineer to build ML and agentic-AI systems that analyze billions of transactions and drive substantial savings. The role focuses on real-time risk decisions, detection logic, and fraud mitigation within Amazon Finance Operations.

You will design scalable ML pipelines, create LLM-powered agents, and develop knowledge graphs and memory layers. Collaboration with scientists, engineers, and finance teams to ship improvements rapidly is expected.

Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture experience.
• Experience programming with at least one software programming language.

Responsibilities

• Design and build ML pipelines that process terabytes of data and score billions of dollars in transactions.
• Build agentic AI applications powered by LLMs with tool interfaces and human-in-the-loop review.
• Develop knowledge and memory systems: vector stores, knowledge graphs, entity-risk layer, in-session and shared memory.
• Evaluate agent effectiveness in fraud detection and translate analyst patterns into reusable workflows.
• Build platform tooling for safe, scalable deployment and governance of detection logic.
• Take models and agents from prototype to production, collaborating with internal customers.

Skills

Non-internship software development

System design & architecture

Programming experience

Education

Bachelor's degree in computer science or equivalent

Tools

ML pipelines

Knowledge graphs

Job description

Do you want to build machine learning and agentic-AI systems that analyze billions of dollars in transactions every day, and measure your impact in millions of dollars saved? In Amazon's Finance Technology group, we build the detection systems (machine learning, and increasingly agentic AI) that defend Amazon against theft, fraud, abuse, and waste across the supply chain, retail catalog, and corporate procurement. We turn terabytes of transaction, vendor, and operational data into real-time risk decisions: scoring payments as they happen, surfacing anomalous behavior, and uncovering collusion networks that span thousands of entities. We're now building the next generation of that platform around generative and agentic AI: multi-agent systems that discover fraud patterns directly from the raw data flowing through Amazon's businesses, working alongside domain experts to turn what they find into production detection logic. The result is a platform where new detection coverage comes not only from engineers, but from agents and the experts who know the fraud best, shipping in days instead of sprints. You'll build the agent tools, ML pipelines, services, and data infrastructure behind all of this, working with generative AI, large language models, and agent frameworks alongside the anomaly-detection, classification, and graph-modeling techniques they build on. You'll partner directly with applied scientists, fellow engineers, and finance operations teams, and you'll see your ideas reach production in weeks, not years. If you want to apply advanced ML and agentic AI at Amazon scale, on systems with a direct, measurable financial impact, we'd love to talk.

Key job responsibilities

You Will Participate In The Full Software Development Lifecycle, From Collaborating With Customers And Scientists On Design, To Building Scalable, Extensible Systems That Run In Production. You Will

Design and build ML pipelines that process terabytes of data and score billions of dollars in transactions.

Build agentic AI applications: LLM-powered agents that discover risk patterns and generate detection logic, operating through well-defined tool interfaces with human-in-the-loop review.

Build the knowledge and memory systems agents depend on: vector stores, knowledge graphs, the entity-risk layer for cross-entity collusion detection, and in-session and shared memory.

Develop how we evaluate agent effectiveness in fraud detection, and turn analysts' ad-hoc investigation patterns into repeatable, templated workflows.

Build the platform and tooling (governed data access, model deployment, and self-service rule authoring) that lets agents and non-engineers ship detection logic safely and fast.

Take models and agents from prototype to reliable, real-time production systems, and work directly with internal customers to turn feedback into shipped improvements.

A day in the life

You’ll partner with applied scientists, software engineers, and finance operations teams across Amazon. You’ll harden an agent pipeline for production, extend the entity graph that powers a new detector, or design a tool interface that lets an agent query data safely, then review it with the customer who’ll use it. Because our team and our customers are comfortable trying new ideas, you’ll get your work in front of real data quickly and iterate on what you learn.

About The Team

We own the machine learning and agentic-AI systems that prevent, recover, and avoid internal and external theft, fraud, abuse, and waste across Amazon Finance Operations. Our platform makes real-time risk decisions on transactions from many of Amazon's largest businesses. We're actively building toward entity-level risk profiles updated in real time, and agentic systems that compress fraud discovery and investigation from weeks to days, with engineers building the leverage layer that multiplies what every analyst and agent can do.

Basic Qualifications

• 3+ years of non-internship professional software development experience
• 2+ 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

Preferred Qualifications

• 3+ 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
• Experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience in processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution)

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: A10439823