Sr Software Development Engineer , Axu

Amazon Amazon · Big Tech · Arlington, VA · Human Resources

Senior Software Development Engineer focused on building and architecting sophisticated AI agent systems leveraging LLM/SLM technologies, Amazon Bedrock's agent core, and custom MCP servers. The role involves creating intelligent automation, deploying ML products, advanced prompt engineering, and integrating agent frameworks to push the boundaries of generative AI for inclusive customer experiences.

What you'd actually do

  1. design and build sophisticated AI agent systems that leverage LLM & SLM technologies
  2. architect scalable solutions using Amazon Bedrock's agent core technologies
  3. develop custom MCP servers
  4. create intelligent automation that transforms how our customers interact with AI
  5. push the boundaries of what's possible with generative AI

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
  • Experience managing and deploying ML products
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
  • Advanced prompt engineering expertise (few-shot, chain-of-thought, ReAct, self-consistency techniques)
  • Hands-on experience with MCP Tools and integrating agent frameworks
  • Strong knowledge of Amazon Bedrock's agents, guardrails, knowledge bases, and model evaluation capabilities

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
  • Experience developing cloud native CI/CD workflows and tools, such as Jenkins, Bamboo, TeamCity, Code Deploy (AWS) or GitLab
  • Experience selling AI/ML solutions
  • Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience with interrupt service routines
  • Experience in A/B testing
  • Experience with retrieval-augmented generation (RAG) using Amazon Bedrock Knowledge Bases and OpenSearch
  • Familiarity with multi-agent orchestration, workflow automation using AWS Step Functions and Bedrock Agents

What the JD emphasized

  • 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
  • Experience managing and deploying ML products
  • Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
  • Advanced prompt engineering expertise (few-shot, chain-of-thought, ReAct, self-consistency techniques)
  • Hands-on experience with MCP Tools and integrating agent frameworks
  • Strong knowledge of Amazon Bedrock's agents, guardrails, knowledge bases, and model evaluation capabilities

Other signals

  • building next-generation AI-powered solutions
  • architecting intelligent agent systems
  • leverage LLM & SLM technologies
  • architect scalable solutions using Amazon Bedrock's agent core technologies
  • develop custom MCP servers
  • create intelligent automation
  • push the boundaries of what's possible with generative AI
  • deploying ML products
  • Advanced prompt engineering expertise
  • integrating agent frameworks
  • Amazon Bedrock's agents, guardrails, knowledge bases, and model evaluation capabilities
  • developing and deploying LLMs in production
  • retrieval-augmented generation (RAG)
  • multi-agent orchestration