Lead Software Engineering

AT&T AT&T · Telecom · Alpharetta, GA

Lead Software Engineer role focused on developing and implementing AI technologies, including LLMs, RAG, and AI-powered chatbots, using frameworks like LangChain and LangGraph. The role involves collaborating on requirements, designing software, executing development methodologies, and performing various testing types, with a strong emphasis on Python, AI, and NoSQL databases.

What you'd actually do

  1. Perform software development by utilizing Python, AI technologies, and NoSQL databases like MongoDB and DynamoDB.
  2. Work with AI, including large language model (LLM) prompts, Retrieval-Augmented Generation (RAG), and AI-powered chatbot/virtual assistants.
  3. Utilize Agenic AI, LangChain, LangGraph, LangSmith, and traditional ML-based AI.
  4. Collaborate to gather and review software requirements/user stories, provide estimates, create software design specifications, and work with engineers/architects to assess and test hardware and software interactions.
  5. Execute a specific development methodology through the application of various programming languages.

Skills

Required

  • Python
  • AI technologies
  • NoSQL databases
  • MongoDB
  • DynamoDB
  • LLM prompts
  • Retrieval-Augmented Generation (RAG)
  • AI-powered chatbot/virtual assistants
  • Agenic AI
  • LangChain
  • LangGraph
  • LangSmith
  • traditional ML-based AI
  • software design
  • automated test plans
  • dynamic application security testing
  • interface testing
  • integration testing
  • end-to-end testing
  • user acceptance testing

Nice to have

  • flex between different technology languages and stacks

What the JD emphasized

  • Requires a Master’s degree, or foreign equivalent degree, in Computer Engineering, Computer Science, or Applied Science and one year of experience in the job offered, or one year of experience in a related occupation performing software development utilizing Python, AI technologies, and NoSQL databases; working with AI, including large language model (LLM)prompts, Retrieval-Augmented Generation (RAG), and AI-powered chatbot/virtual assistants; utilizing Agenic AI, LangChain, LangGraph, LangSmith, and traditional ML-based AI.

Other signals

  • Utilize AI, including large language model (LLM) prompts, Retrieval-Augmented Generation (RAG), and AI-powered chatbot/virtual assistants.
  • Utilize Agenic AI, LangChain, LangGraph, LangSmith, and traditional ML-based AI.