Sr. Full Stack AI Engineer
Listed on 2026-04-23
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Software Development
AI Engineer, Full Stack Developer, Cloud Engineer - Software
Senior Staff Software Engineer – IE07HE
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals — and to help others accomplish theirs, too. Join our team as we help shape the future.
Full Stack Engineer — AI-Augmented Development Position SummaryWe are seeking a highly skilled Full Stack Engineer who combines deep software engineering expertise with advanced proficiency in AI-powered development tools. This role is focused on hands‑on building and delivery — a practitioner who ships production-quality code end-to-end across the stack while leveraging AI to accelerate development velocity, improve code quality, and drive innovation.
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).
Key Responsibilities Hands‑On Build & Delivery- Own features from concept through production release, writing and shipping high-quality code daily
- Build, test, deploy, and iterate rapidly across frontend, backend, APIs, and data layers
- Troubleshoot and resolve production issues, performance bottlenecks, and complex bugs
- Implement and maintain CI/CD pipelines, automated testing, and deployment automation
- Contribute to architectural decisions and design discussions as a practitioner, ensuring designs translate into solid implementations
- Own system reliability, performance, and security for the services you build
- Build and ship modern frontend applications using frameworks such as React, Angular, or Vue.js with Type Script
- Develop, deploy, and operate robust backend services using Java (Spring Boot), Node.js, Python, or .NET
- Implement and optimize RESTful APIs, Graph
QL endpoints, and event-driven integrations - Configure and manage cloud-native infrastructure (AWS or GCP) including containers, serverless, and infrastructure-as-code
- Build and tune data layers across relational and No
SQL databases, caching, and message queues - Write clean, well‑tested, production-ready code with a focus on maintainability and operational excellence
- Leverage AI coding assistants (Git Hub Copilot, Cursor, Claude Opus, etc.) to dramatically accelerate development workflows
- Use AI tools for code generation, refactoring, test writing, documentation, and code review
- Integrate large language model (LLM) APIs and AI/ML services into applications (e.g., OpenAI, GCP Vertex, AWS Bedrock)
- Design and implement RAG (Retrieval-Augmented Generation) pipelines, prompt engineering strategies, and AI-powered features
- Evaluate, select, and champion AI tools and practices that improve team productivity
- Develop custom agents, workflows, and automations using AI platforms and frameworks (Vertex Studio, Semantic Kernel, CrewAI, etc.)
- Establish guardrails, security practices, and governance for responsible AI usage in engineering
- Influence engineering culture by evangelizing AI-augmented development practices
- Train and upskill team members on effective use of AI tools in their daily workflows
- Contribute to internal knowledge bases, tech talks, and communities of practice
- Partner with product, design, and data science teams to identify AI-driven opportunities
- Experience:
10 years of professional software engineering experience, with 5 years in hands‑on full stack delivery roles - Education:
Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent experience) - Frontend:
Expert-level proficiency building production applications with modern JavaScript/Type Script frameworks (React, Angular, or Vue.js), HTML5, CSS3, responsive design, and accessibility standards - Backend:
Deep hands‑on experience building and operating services with Java/Spring Boot, Node.js/Express, Python/FastAPI/Django, or C#/.NET - Cloud & Dev Ops:
Strong hands‑on experience deploying and operating on cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD tooling (Jenkins, Git Hub Actions, Git…
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