Sr. Software Development Engineer, Bedrock Agentcore Knowledge Bases

Amazon Amazon · Big Tech · NY +1 · Software Development

Senior Software Development Engineer to lead architecture and design of AI data pipelines and large-scale distributed systems for Amazon Bedrock Knowledge Bases, a RAG service for enterprise data integration with FMs and agents. Focus on scaling services, innovating on Gen AI, and ensuring extensible, performant, and secure solutions.

What you'd actually do

  1. Lead the design and implementation of distributed AI data pipelines and systems, providing system-wide architectural guidance
  2. Balance speed of execution with architectural requirements, identifying one-way door decisions that require the right long-term solution
  3. Drive adoption of engineering best practices and operational excellence across the team
  4. Solve complex technical problems with multiple risks and roadblocks, bringing clarity through simple, well-designed solutions
  5. Mentor and coach multiple engineers, helping develop the next generation of technical talent

Skills

Required

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team

Nice to have

  • 5+ 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

  • high-scale distributed systems
  • Gen AI
  • Amazon Bedrock Knowledge Bases
  • end-to-end Retrieval Augmented Generation (RAG) workflow
  • enterprise data
  • Foundation Models (FM)
  • agents
  • data sources
  • response quality
  • new content types and modality
  • AI data pipeline
  • large-scale distributed systems
  • technical leadership
  • team-level architecture
  • complex problems
  • technical roadmap
  • extensible, performant, and secure
  • operational excellence
  • state-of-the-art Generative AI technology
  • Retrieval Augmented Generation

Other signals

  • Amazon Bedrock Knowledge Bases
  • Retrieval Augmented Generation (RAG)
  • end-to-end workflow
  • contextual information from enterprise data
  • Foundation Models (FM)
  • agents
  • data sources
  • response quality
  • new content types and modality
  • AI data pipeline
  • large-scale distributed systems
  • technical leadership
  • team-level architecture
  • complex problems
  • technical roadmap
  • extensible, performant, and secure solutions
  • operational excellence
  • state-of-the-art Generative AI technology