Full Stack Staff Software Engineer — AI-Augmented Development

This role follows a hybrid work schedule. Candidates who live near one of our office locations are expected to work in the office three days per 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

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

Required Qualifications

Experience: 10+ years of professional software engineering experience, with 5+ years in hands-on full stack tech lead 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), 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

Cloud & DevOps: Strong hands-on experience deploying and operating on cloud platforms (AWS, GCP), 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

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.)

Technical Competencies:

Domain Expected Proficiency

Frontend Development: Advanced

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

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).

Candidates 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.

Compensation

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:

$116,000 - $174,000

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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