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Software Development Engineer, Eva Development Team

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Amazon
Full Time position
Listed on 2026-10-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), AWS, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 144000 - 194000 USD Yearly USD 144000.00 194000.00 YEAR
Job Description & How to Apply Below

Software Development Engineer, Eva Development Team

o:  | Amazon Data Services, Inc.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

About the Data Center Gen AI Team

Join the Data Center Gen AI team, where we build generative AI solutions for AWS data centers. Our systems orchestrate physical work processes across AWS's worldwide data centers, directly impacting millions of customers who rely on AWS services.

Position Impact

You’ll contribute to transforming data center operations through AI/ML innovations, helping build the platform primitives that dozens of teams across the Data Center Community rely on. You’ll work on developing intelligent systems that optimize technician workflows, automate decision‑making processes, and enhance operational efficiency across AWS's global infrastructure while supporting AI-powered capabilities for a 30K+ globally distributed user base.

Strong familiarity with one or more of the following:

  • Generative AI / Agentic Systems — LLM integration, prompt engineering, RAG architectures, tool‑calling patterns, agent frameworks (Strands, Lang Chain)
  • Full-Stack Serverless Engineering — AWS Lambda, API Gateway, Cloud Front, DynamoDB/RDS, Event Bridge, SQS, CDK Infrastructure-as-Code
  • Frontend & SDK Development — React, Type Script, Clouds cape Design System, component library development, streaming interfaces (SSE)
  • Search & Knowledge Systems — Open Search/Elasticsearch, vector embeddings, hybrid retrieval, document processing pipelines, semantic chunking
  • ML & Data Engineering — Sage Maker, time-series analysis, anomaly detection, classification models, feature engineering, ETL pipelines
  • Platform & Dev Ops — CI/CD pipeline development, progressive deployment, synthetic monitoring, observability (Cloud Watch, X-Ray, Open Telemetry)

Ideal Candidate Profile

  • Thrives in ambiguous environments and is eager to learn and adapt quickly
  • Demonstrates a bias for action with the ability to deliver results in fast‑paced settings
  • Builds and maintains solid technical depth while staying customer-focused
  • Shows genuine curiosity and enthusiasm for AI/ML advancements
  • Has working knowledge of AI/ML technology application (LLMs, agents, RAG, Skills, ML models)
  • Takes ownership of features and components end‑to‑end, driving them to completion with guidance from senior engineers
  • Balances pragmatic execution with creative problem‑solving

This role offers the opportunity to contribute to the future of AWS data center operations through innovative AI/ML solutions while working with advanced technologies at unprecedented scale.

Key job responsibilities

  • Design and develop AI/ML platform features and solutions, contributing to systems that serve both data center operations and engineering teams
  • Own end‑to‑end delivery of features and components, including AI integrations, deployment pipelines,…
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