Software Engineer (ai/genai Platforms)

Allstate Allstate · Insurance · Charlotte +3

Software Engineer focused on building AI/GenAI/Agentic AI capabilities on an Unstructured Data Platform, transforming enterprise data into actionable intelligence and autonomous AI systems. Requires Python/Java, experience with LLMs, RAG, Vector Search, Multimodal AI, AI Agents, Prompt Engineering, and cloud platforms like AWS.

What you'd actually do

  1. design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power next‑generation enterprise capabilities.
  2. build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power next‑generation enterprise capabilities.
  3. design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI to power next‑generation enterprise capabilities.

Skills

Required

  • Python
  • Java
  • Large Language Models (LLMs)
  • Retrieval Augmented Generation (RAG)
  • Vector Search & Embeddings
  • Multimodal AI
  • AI Agents / Agent Frameworks
  • Prompt Engineering
  • Semantic Models
  • LangChain
  • LlamaIndex
  • Semantic Kernel
  • Hugging Face
  • OpenAI
  • AWS Bedrock
  • Azure OpenAI
  • Data lakes and lakehouse architectures
  • Microsoft Fabric
  • Azure Fabric
  • Kafka
  • Amazon Web Services (AWS)
  • MongoDB Atlas
  • Amazon DocumentDB
  • Amazon SageMaker
  • Model training, evaluation, and deployment
  • MLOps workflows
  • Monitoring and troubleshooting AI and data pipelines
  • Datadog
  • AWS CloudWatch

Nice to have

  • Vector databases

What the JD emphasized

  • Python (required)
  • Java, with hands-on experience building backend services and enterprise integrations
  • Ability to work across both Python and Java codebases, integrating AI/ML components into Java-based enterprise systems
  • Proven experience building and operating production-grade AI/ML systems
  • Strong understanding of data pipelines and distributed data processing

Other signals

  • building cutting-edge AI, GenAI, and Agentic AI capabilities
  • transform massive volumes of documents, voice recordings, images, and video into actionable intelligence, powerful insights, and autonomous AI systems
  • design and build AI-driven systems that combine large-scale data engineering, machine learning, and generative AI