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# Full Stack Engineer — AI-Augmented Development
## Position Summary
We 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).
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## 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
### Full Stack Implementation
- Build and ship modern frontend applications using frameworks such as React, Angular, or Vue.js with TypeScript
- Develop, deploy, and operate robust backend services using Java (Spring Boot), Node.js, Python, or .NET
- Implement and optimize RESTful APIs, GraphQL 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 NoSQL databases, caching, and message queues
- Write clean, well-tested, production-ready code with a focus on maintainability and operational excellence
### AI-Augmented Development
- Leverage AI coding assistants (GitHub 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
### Technical Leadership & Mentorship
- 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
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## Required Qualifications
- **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/TypeScript 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 & DevOps:** Strong hands-on experience deploying and operating on cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD tooling (Jenkins, GitHub Actions, GitLab CI)
- **Data:** Proficiency building and optimizing data layers with SQL and NoSQL databases (PostgreSQL, MongoDB, DynamoDB, Redis), data modeling, and query tuning
- **API Implementation:** Proven track record building RESTful APIs, GraphQL services, gRPC endpoints, or event-driven integrations (Kafka, RabbitMQ)
- **AI Tools Proficiency:**
- Advanced daily usage of AI coding assistants (GitHub Copilot, Cursor, or equivalent)
- Experience integrating LLM APIs (OpenAI, Anthropic, GCP Vertex Service) into production applications
- Familiarity with prompt engineering, fine-tuning, embeddings, and vector databases
- Track record of measurably improving team velocity through AI tool adoption
- **Testing:** Strong testing practices including unit, integration, and end-to-end testing with modern frameworks
- **Architecture:** Working knowledge of distributed systems, microservices, and event-driven patterns; ability to contribute to and implement architectural designs
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## Preferred Qualifications
- Experience building AI/ML-powered product features (chatbots, intelligent search, recommendation engines, content generation)
- Familiarity with AI orchestration frameworks (LangChain, Semantic Kernel, AutoGen, CrewAI)
- Experience with agent-based AI architectures and autonomous workflows
- Contributions to open-source projects or published technical content
- Experience in regulated industries (insurance, finance, healthcare) with security and compliance requirements
- Certifications in cloud platforms (AWS Solutions Architect, GCP Professional Cloud Architect, etc.)
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## Technical Competencies
| Domain | Expected Proficiency |
|---|---|
| Frontend Development | Expert |
| Backend Development | Expert |
| Cloud & Infrastructure | Advanced |
| CI/CD & DevOps | Advanced |
| System Design & Architecture | Advanced |
| AI Tools & Copilots | Expert |
| LLM Integration & Prompt Engineering | Advanced |
| Security & Compliance | Advanced |
| Testing & Quality | Expert |
| Mentorship & Leadership | Advanced |
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Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
