HITL Platform Engineer for AI Customer Service

Amazon Inc.; Asti; Ibrido; EUR 127.000 - 171.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

RSUs (Restricted Stock Units)

401(k) matching

Paid time off

Descrizione del lavoro

Amazon is seeking a Software Development Engineer to help build the HITL platform for Amazon Customer Service. You will own components end to end, from design documentation through production launch, and you will influence latency budgets, reliability, and platform guarantees in live customer conversations.

You will collaborate with applied scientists to productionize ML components, work with dependent teams, and mentor engineers while shaping the team's architectural direction.

Competenze

• 3+ years of non-internship professional software development experience.
• 2+ years of design or architecture (patterns, reliability, scaling) of systems.
• 2+ years of designing and developing large-scale, multi-tiered software in languages such as C#, C++, Java, or Perl.

Mansioni

• Own the design and delivery of major HITL components from design through production launch.
• Decouple HITL into a standalone platform and define service contracts for onboarding new bots/usages.
• Make architectural decisions on latency, reliability, and failure handling for live conversations.
• Partner with scientists to productionize ML components, including context summarization and proactive questioning.
• Drive operational excellence with metrics, alarms, and on-call ownership for your systems.
• Mentor engineers and participate in design reviews to uphold coding standards.

Conoscenze

C#

C++

Java

Perl

OO design

Formazione

Bachelor's degree in CS/Engineering/Math

Descrizione del lavoro

Amazon is seeking a Software Development Engineer to help build the HITL platform for Amazon Customer Service. You will own components end to end, from design documentation through production launch, and you will influence latency budgets, reliability, and platform guarantees in live customer conversations.

You will collaborate with applied scientists to productionize ML components, work with dependent teams, and mentor engineers while shaping the team's architectural direction.