Staff Software Engineer (UI & Applied AI)

The Hartford•Hartford, CT

1d•Hybrid

About The Position

Staff Software Engineer - IE07IE 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. The Hartford is seeking a Staff Software Engineer (UI & Applied AI) to join the Innovation Value Stream within Personal Lines—an area where engineers help set the trend for AI platforms across the PL business. This is a rare opportunity to work on a greenfield initiative, shaping how The Hartford designs and delivers next‑generation AI‑enabled user experiences. In this role, you will define and build the UI foundation for emerging AI and agentic capabilities, including chat experiences, AI assistant panels (copilots), file‑upload for RAG pipelines, agent tools, MCP‑based interactions, and integration with API gateways exposing agent ADK runner . You will work directly with a collaborative, product‑based team that values: Rapid prototyping to prove ideas early Enterprise best practices and alignment with EA and AI governance Continuous learning and experimentation Delivering cutting-edge experiences that create measurable value for cross-functional Personal Lines users (pricing analysts, CSRs, inspection contractors, underwriting, and product partners) This role offers the opportunity to make a significant strategic and technical impact, influencing the future of AI‑driven application experiences across the Personal Lines organization.

Requirements

8+ years building complex, production single‑page applications with TypeScript.
Expertise with Angular (v14+) and/or React, including hooks, state management, routing, forms, and component architecture.
Hands-on experience with SSR/CSR patterns and frameworks (Angular Universal, Next.js).
Hands-on LLM integration: retrieval/embeddings, tool/function calling, streaming responses, and assistant/chat UIs.
Familiarity with MCP, agent tools, and API gateways exposing runnables.
Cloud-native experience with GCP and/or AWS; integration with Snowflake/data products, CI/CD pipelines, and feature flags.
Production performance engineering experience: modular routing, lazy loading, async state patterns, bundle control, render efficiency.
Monitoring and observability with Dynatrace, Google Analytics, Cloud Logging, and Splunk.
Strong foundational skills in HTML, CSS, JavaScript/TypeScript, REST APIs.
Excellent analytical, problem-solving, communication, and collaboration skills.
Experience in Agile/Scrum environments.
Curiosity, initiative, and a passion for learning modern technologies and participating in internal communities.
Candidates must be authorized to work in the US without company sponsorship.

Nice To Haves

Micro-frontends (Module Federation).
Schema-first API contracts (OpenAPI, GraphQL).
Real-time UX patterns (SSE/WebSockets).
Experience with P&C Insurance workflows (rating, underwriting, CSR, inspections).
Background working with document ingestion pipelines, RAG, or agentic document workflows.

Responsibilities

Define and evolve the UI platform strategy, ensuring extensibility, future‑proofing, and readiness for rapidly emerging AI capabilities (interact with agent workflows, interactive chat, Agent 2 Agent, agent tool use selection, RAG workflows).
Provide technical leadership, maintaining architectural alignment and the integrity of the UI platform and application environment.
Collaborate with platform teams to safely leverage AI and agentic capabilities through stable, versioned APIs and shared governance.
Champion innovation, experimenting with modern frameworks, architectures, and AI-driven enhancements that improve user experience and accelerate delivery.
Partner with Product, Design, Architecture, Data Science, and Platform teams to evolve ideas from POCs → MVPs → scalable production experiences.
Design human‑in‑the-loop workflows (approve/override/rollback, review gates, clear status indicators) to ensure safe and transparent AI decision-making.
Plan integration patterns for GCP Agent SDK/Agent Builder, AWS Bedrock/Anthropic, Snowflake/data products, and retrieval/embedding pipelines using typed SDKs/APIs.
Architect AI UX patterns such as copilots, chat flows, inline recommendations, tool-triggering actions, and token‑streaming guidance with cancel/retry and partial updates.
Define prompt templates, guardrails, and explainability signals (confidence, sources, metadata) for safe AI usage directly in the UI flows.
Lead hands‑on UI development in TypeScript using Angular and/or React, delivering modern single-page applications across CSR, SSR, and hybrid rendering models (Angular Universal, Next.js).
Build AI-driven user interaction surfaces: side panels, chats, inline instruction flows, streaming experiences, and contextual tool invocation.
Develop file-upload and document‑management interfaces integrated with RAG pipelines, presenting detailed ingestion lifecycle statuses (uploaded → queued → extraction → embedding → retrieval-ready → processed).
Integrate UI components with MCP (Model Context Protocol), agent tools, and API gateways, supporting multi-step agent workflows (planning → executing → tool call → validating → complete → error).
Improve UI performance through modular routing, lazy loading, optimal async patterns, reduced bundle sizes, efficient rendering, and clean component architecture.
Apply strong engineering practices: unit tests, integration tests, E2E, visual regression, prompt regression, and streaming/real-time test harnesses.
Monitor real‑world performance and reliability using Dynatrace, Google Analytics, Cloud Logging, and Splunk, ensuring resilience and responsiveness.
Track behavior of AI workflows, tool interactions, streaming performance, and user flows to ensure correctness and minimize latency or failure modes.
Conduct code reviews focused on accessibility, maintainability, reliability, and adherence to engineering best practices.
Mentor junior engineers and raise overall engineering craftsmanship across the team.
Communicate risks, issues, decisions, and technical trade-offs proactively to stakeholders and leadership.
Provide ongoing support for platform evolution, architectural governance, and new AI capability onboarding.