Software Engineer: Automation/ai - Level 3 (chandler)

Northrop Grumman Northrop Grumman · Aerospace · Chandler, AZ +1 · Software

Software Engineer with expertise in C++ and Python, focusing on designing, developing, and maintaining software solutions, managing DevOps processes, automating workflows with CI/CD pipelines, and supporting containerized development environments and infrastructure. The role involves developing and deploying AI/ML solutions, integrating models into applications or agentic frameworks, understanding LLMs, hosting AI/ML models in cloud or on-premise environments, and utilizing vector databases and RAG techniques.

What you'd actually do

  1. Design, develop, document, test, and debug application software and systems
  2. Automate workflows and processes by building and maintaining CI/CD pipelines within a DevOps environment.
  3. Develop and maintain containerized applications to ensure portability, scalability, and reliability.
  4. Create and manage Ansible playbooks to automate deployment and configuration processes.
  5. Provide infrastructure support by troubleshooting, optimizing performance, and maintaining high availability of systems.

Skills

Required

  • C++
  • Python
  • DevOps
  • CI/CD pipelines
  • containerized development environments
  • Ansible
  • Linux environments
  • scripting
  • system configuration
  • GitLab CI/CD
  • version control systems
  • APIs
  • Mastra
  • LangChain
  • Large Language Models (LLMs)
  • fine-tuning
  • hosting
  • inference optimization
  • cloud-based environments
  • AWS
  • Azure
  • GCP
  • on-premise containerized infrastructure
  • vector databases
  • retrieval-augmented generation (RAG)
  • embedding-based search

Nice to have

  • GOLang
  • Active DoD Secret Security Clearance

What the JD emphasized

  • Must have the ability to obtain and maintain a U.S. Government DoD Secret security clearance
  • Demonstrated experience developing and deploying AI and/or Machine Learning (ML) solutions
  • Familiarity with APIs and integrating models into applications or agentic frameworks such as Mastra, LangChain, or other similar toolkits for building autonomous agents.
  • Strong understanding of Large Language Models (LLMs), including fine-tuning, hosting, and inference optimization.
  • Experience with developing and hosting AI/ML models in cloud-based environments (e.g., AWS, Azure, or GCP) or on-premise containerized infrastructure.
  • Familiarity with vector databases, retrieval-augmented generation (RAG) techniques, and embedding-based search for AI-driven systems.

Other signals

  • Develop and deploy AI and/or Machine Learning (ML) solutions
  • Familiarity with APIs and integrating models into applications or agentic frameworks such as Mastra, LangChain
  • Strong understanding of Large Language Models (LLMs), including fine-tuning, hosting, and inference optimization
  • Experience with developing and hosting AI/ML models in cloud-based environments or on-premise containerized infrastructure
  • Familiarity with vector databases, retrieval-augmented generation (RAG) techniques, and embedding-based search for AI-driven systems