System Development Engineer, Legal Technology

Amazon Amazon · Big Tech · Seattle, WA · Systems, Quality, & Security Engineering

System Development Engineer role focused on AI/ML automation and integration within a legal technology context, modernizing infrastructure and eliminating manual tasks.

What you'd actually do

  1. Lead and contribute to strategic initiatives around AI/ML automation, integration, and knowledge management, establishing new capabilities and best practices for the team
  2. Design and implement automation solutions that integrate with third-party tools via APIs, reducing manual effort for Legal department customers and improving data accuracy and timeliness
  3. Lead the modernization and migration of on-premises services to cloud-based infrastructure on AWS, ensuring reliability, security, and operational efficiency
  4. Write, maintain, and enhance code for operational improvements including automated security updates, data synchronization, and system monitoring
  5. Collaborate with cross-functional teams to understand customer needs, identify automation opportunities, and translate requirements into technical solutions

Skills

Required

  • automating, deploying, and supporting large-scale infrastructure
  • programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
  • Linux/Unix
  • CI/CD pipelines build processes
  • 3+ years of working with windows server technologies experience
  • AI/ML technologies
  • AWS Services including EC2, Lambda, S3, DynamoDB, SQS

Nice to have

  • distributed systems at scale
  • writing and publishing technical documents or equivalent
  • working with and managing third party vendors

What the JD emphasized

  • AI/ML automation
  • integration
  • knowledge management
  • automation solutions
  • API integration
  • cloud infrastructure
  • LLM-based automation

Other signals

  • AI/ML automation
  • integration
  • knowledge management
  • automation solutions
  • API integration
  • cloud infrastructure
  • LLM-based automation