Managing Engineer - Risk Data & AI (Remote, US)

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 Risk Data & AI designs, builds, and operates governed data products, analytics solutions, and AI-enabled capabilities that support risk and compliance decision-making. The team applies modern data, software, and AI engineering practices to deliver scalable data pipelines, trusted analytical products, intelligent automation, and responsible AI solutions that enable TORC to identify emerging risks, generate actionable insights, and make timely, evidence-based decisions. The Managing Engineer is a hands-on engineering leader responsible for leading teams that build, deliver, and operate these data and AI products in production. This role blends strong technical leadership, people leadership, and delivery ownership, ensuring solutions are scalable, reliable, secure, and responsibly implemented, with measurable business and engineering impact. Key Responsibilities • Lead and manage a team delivering data products, AI-enabled applications, intelligent automation capabilities, and enterprise data platforms. • Set technical direction across data engineering, AI engineering, application development, deployment, and operational support. • Act as a hands-on leader contributing to architecture, design decisions, AI solution patterns, and critical-path development. • Own production outcomes including system reliability, data quality, application performance, model effectiveness, and operational health. • Partner with Digital Product Managers, data teams, AI teams, and engineering organizations to align roadmaps, priorities, and delivery outcomes. • Drive modern engineering practices including TDD, CI/CD, observability, MLOps, automated testing, and responsible AI implementation. • Translate business, risk, and compliance requirements into scalable data, analytics, and AI-powered solutions and reusable engineering patterns. • Influence adoption of enterprise data standards, AI engineering best practices, and platform-integrated capabilities. • Lead agile execution with a strong focus on measurable business outcomes, engineering excellence, and continuous delivery. Required Skills: • 5+ years of data, analytics, or AI engineering experience with hands-on development in Python and/or Java, and delivery of production-grade AI solutions. • 2+ years leading engineers with technical guidance across architecture, design, code reviews, engineering standards, and delivery coaching. • Experience with APIs, backend services, data pipelines, and analytical/reporting systems. • Experience delivering AI-enabled applications, Generative AI solutions, or intelligent automation capabilities. • Knowledge of modern engineering practices including DevSecOps, CI/CD pipelines, testing, monitoring, and observability. • Experience with Generative AI frameworks, large language models, prompt engineering, and AI orchestration frameworks. • Experience building Retrieval-Augmented Generation (RAG) solutions using enterprise data and vector databases. • Experience working in agile environments delivering data, analytics, or AI solutions. Desirable Skills: • Experience in risk, compliance, security, governance, or technology operations domains. • Experience with MLOps, AI model deployment, evaluation, monitoring, and operationalization. • Exposure to agentic AI, multi-agent systems, AI copilots, or intelligent wor