[Hiring] Software Engineer Consultant II @Allstate

Role Description

The Full Stack Developer is a hands-on, full-stack engineer responsible for designing, developing, and supporting enterprise applications and integrations that enable critical business operations. This role spans backend systems, frontend UI, and integration layers, delivering secure, scalable, and high-quality solutions that meet business needs. This includes hands-on experience integrating with Azure AI services such as Azure OpenAI Service and Azure AI Search.

• Design, develop, test, and deploy full-stack features using Java/Spring Boot, Python, and React.
• Build and maintain secure, scalable RESTful APIs and backend microservices.
• Develop responsive, reusable UI components and workflows in React.
• Implement system integrations across internal applications and external vendor platforms.
• Develop and enhance chatbot user interfaces within React applications.
• Build conversational UI features such as:
  • Message streams and interaction flows
  • Structured and unstructured response rendering
  • User input handling and validation
  • Real-time integration with backend services
  • Real-time integration with AI/LLM services
• Ensure the chatbot UI delivers a seamless, intuitive, and accessible user experience.

Qualifications

• 2 or more years of professional experience in full-stack development.
• Strong hands-on expertise in:
  • Java / Spring Boot (backend APIs, microservices)
  • Python (automation, backend services)
  • React with TypeScript/JavaScript (modern UI development)
• Hands-on experience building chatbot UI features in a production setting.
• Strong understanding of microservices architecture and cloud-native principles.
• Experience with:
  • Docker & Kubernetes
  • Relational and/or NoSQL databases (MS SQL, PostgreSQL, MongoDB, DocumentDB)

Requirements

• Strong understanding of LLM integration concepts, including prompt engineering, retrieval-augmented generation (RAG), and model serving pipelines.
• Familiarity with MLOps practices, including CI/CD, production monitoring, and deployment in cloud environments such as Azure and AWS.
• Experience supporting MLOps workflows for dataset creation, management, and analysis to support model training and evaluation.

Benefits

• Compensation offered for this role is $70,100.00 - $121,475.00 annually and is based on experience and qualifications.