Software Engineer Consultant II
AllstateAbout the role
At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.
Job Description
Software Engineer Consultant IIAbout Law & Regulations
Law & Regulations delivers expert legal services that protect Allstate and its customers while ensuring compliance with evolving regulatory and ethical standards. We provide comprehensive support across claims litigation, complex corporate transactions, and enterprisewide compliance programs, enabling the business to confidently navigate today’s legal landscape.
By leveraging innovative legal strategies and modern technology, we promote seamless collaboration, proactive risk management, and effective problem solving across the organization. We demonstrate our core values through integrity, accountability, collaboration, and excellence. We are trusted legal advisors who place the needs of our customers and business partners at the heart of everything we do. We value each other, seek feedback, and take meaningful action to continuously improve.
Our collective success is enabled by collaboration across all areas of responsibility within Allstate and by upholding the legal and ethical foundation that drives business performance.
What We Deliver
Exceptional Legal Support: Expert counsel and representation that safeguard Allstate’s interests and support our customers.
Compliance & Ethical Governance: Oversight of enterprisewide privacy, regulatory compliance, and ethics programs.
Innovative Legal Operations: Use of agile processes and modern technologies to enhance operational efficiency and service delivery.
The Full Stack Developer is a handson, fullstack 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 highquality solutions that meet business needs. This includes hands-on experience integrating with Azure AI services such as Azure OpenAI Service and Azure AI Search.
The ideal candidate demonstrates strong technical execution, effective problemsolving abilities, and the ability to work successfully within a largescale enterprise environment that requires adherence to governance, compliance, and security standards. The role includes partial ownership of technical solutions and active participation in design and architectural discussions. This includes a strong understanding of LLM integration concepts such as 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, and experience supporting MLOps workflows for dataset creation, management, and analysis to support model training and evaluation.
Design, develop, test, and deploy fullstack 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
- realtime integration with backend services
- realtime integration with AI/LLM services
Ensure the chatbot UI delivers a seamless, intuitive, and accessible user experience.
Hands-on experience integrating with Azure AI services such as Azure OpenAI Service and Azure AI Search.
Strong understanding of LLM integration concepts, including prompt engineering, retrieval-augmented generation (RAG), and model serving pipelines.
Cloud, DevOps & Operations
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