Software Development Engineer Ii, Fintech

Amazon Amazon · Big Tech · IN, TS, Hyderabad · Software Development

Software Development Engineer II for the FinTech Lyra (Liquidity, Risk and Applied AI) team. The role involves designing, developing, and owning scalable distributed systems for critical financial workflows, including risk engines. Collaboration with ML scientists, data scientists, and other stakeholders is key to translating business requirements into technical solutions. The team focuses on managing and optimizing liquidity needs and risk exposure, ensuring controllership and compliance.

What you'd actually do

  1. Design, develop, and own scalable distributed systems that power critical financial workflows, including risk engines that calculate Amazon's risk profile and assess the incurred cost to insure these risks.
  2. Collaborate closely with machine learning scientists, data scientists, software engineers, risk managers, product managers, and business stakeholders across Finance globally to translate complex business requirements into robust technical solutions.
  3. Play a role in the design, implementation and deployment of large-scale and complex software systems.
  4. Deliver innovative solutions to challenging problems.
  5. Communicate your ideas effectively to achieve the right outcome for your team and customer.

Skills

Required

  • 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

Nice to have

  • 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

What the JD emphasized

  • Applied AI

Other signals

  • design, develop, and own scalable distributed systems that power critical financial workflows, including risk engines
  • collaborate closely with machine learning scientists, data scientists, software engineers, risk managers, product managers, and business stakeholders
  • translate complex business requirements into robust technical solutions