Software Engineer Lead Consultant

Allstate Allstate · Insurance · SC · Remote

Software Engineer Lead Consultant at Allstate, focusing on full-stack application development using modern, AI-augmented engineering practices. The role involves developing and enhancing features with Java, Spring Boot, and React, participating in agile processes, and contributing to CI/CD pipelines. Emphasizes TDD, pair programming, and secure coding practices, with a strong understanding of AI-generated code evaluation. The role is an individual contributor and does not involve supervisory responsibilities.

What you'd actually do

  1. Develop and enhance full‑stack features in alignment with established architecture and design guidelines.
  2. Implement backend services using Java and Spring Boot, and frontend components using React.
  3. Participate in daily standups, backlog refinement, iteration planning, and retrospectives.
  4. Collaborate with product managers, designers, and engineering peers to clarify requirements and contribute technical input.
  5. Contribute to CI/CD pipelines and support reliable deployment practices.

Skills

Required

  • 5+ years of professional software engineering experience
  • Java
  • Spring Boot
  • React
  • modern front‑end development practices
  • SQL experience with MSSQL, ORACLE, or equivalent
  • building and consuming RESTful APIs
  • object-oriented programming
  • design principles (SOLID)
  • Twelve-factor app
  • secure coding practices (e.g., OWASP Top 10, input validation, authentication/authorization patterns)
  • paired programming
  • TDD
  • Git
  • Unit and integration testing (e.g., JUnit, Mockito, Jest, React Testing Library)
  • CI/CD pipelines (e.g., Jenkins, GitHub Actions)
  • Docker or containerized environments
  • cloud environments (Kubernetes, AWS)
  • Frontend fundamentals: HTML5, CSS3, JavaScript/TypeScript
  • event-driven architecture
  • messaging systems (e.g., Apache Kafka)
  • architect and deliver working features end-to-end with velocity

Nice to have

  • ORM experience (e.g., Hibernate/JPA)
  • frontend state management tools
  • Basic performance monitoring and optimization
  • microservices or distributed system environment
  • leveraging generative AI and LLMs to enhance development productivity, automate workflows, or build intelligent features
  • Secrets management (e.g., HashiCorp Vault)
  • database migration tooling (e.g., Flyway)
  • Serverless Functions (Azure Functions, AWS Lambda, or similar)
  • GitHub Actions (advanced workflows, automation, environment strategies)
  • GitOps principles or tooling (e.g., Argo CD, Flux)

What the JD emphasized

  • AI-augmented engineering practices
  • critically evaluate AI-generated code for security and correctness
  • Proficiency with AI-assisted development tools (e.g., GitHub Copilot, AI code assistants) for accelerating development workflows