Senior Software Engineer, AI-Driven Systems

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Software Engineer, AI-Driven Systems based in the United States.

The Senior Software Engineer will help shape the next generation of a modern, AI-native insurance technology platform. In this hands-on role, you will redesign backend architecture, build durable workflows, and modernize distributed systems while maintaining the reliability of live production services. You will use AI coding agents as a core part of your daily engineering workflow, combining advanced automation with rigorous testing, code quality, and technical judgment. Working primarily with Node.js, TypeScript, and AWS, you will establish reusable engineering patterns that enable teams to deliver software faster and more consistently. You will also contribute to the development of AI infrastructure, including Model Context Protocol (MCP) tooling, automated evaluations, and agent-driven workflows. This fully remote opportunity offers the autonomy of a fast-moving technology environment, with the stability and resources of an established global insurance organization.

Accountabilities:

• Design and develop durable backend workflows: Architect and implement reliable services that replace existing event-driven processes, defining clear service boundaries, state ownership, idempotency, retry strategies, and workflow orchestration.
• Write and ship production code: Develop, review, test, and deploy high-quality Node.js and TypeScript code daily, using AI coding agents such as Claude Code as primary engineering partners.
• Lead AI-assisted development: Apply agentic coding tools to complex engineering challenges by establishing the right context, breaking down tasks, guiding execution, and carefully validating generated code.
• Establish reusable engineering standards: Create reference architectures, service templates, shared libraries, and code generators that standardize implementation practices across the evolving platform.
• Drive large-scale system modernization: Plan and execute incremental migrations, framework upgrades, service rewrites, and architectural improvements while maintaining production continuity and implementing thoroughly tested rollback strategies.
• Build AI engineering infrastructure: Develop and maintain MCP servers, agent tooling, evaluation scripts, automated checks, and supporting infrastructure to ensure AI-generated code meets the same quality, security, and reliability standards as manually written code.
• Ensure production reliability: Instrument services with metrics, alerts, dashboards, and distributed tracing, monitor system health, investigate failures, and take end-to-end ownership of production incidents and their resolution.
• Contribute to frontend integration: Make targeted changes to React and Angular applications when necessary to support backend development, investigate issues across application layers, and ensure consistent end-to-end functionality.
• Collaborate across technical and business teams: Partner with product, growth, and engineering colleagues to translate business needs into technical solutions, participate in architecture discussions, and contribute to constructive code reviews.
• Improve engineering productivity: Identify opportunities to simplify development workflows, strengthen automated testing, reduce repetitive work, and increase the effectiveness of AI-assisted software delivery.
• Support continuous technical improvement: Evaluate emerging approaches to agentic development, workflow orchestration, and AI-native architecture, introducing practical innovations that improve scalability, maintainability, and delivery speed.

Requirements:

• Backend engineering expertise: Strong professional experience developing, deploying, and maintaining production applications using Node.js and TypeScript, with the ability to contribute effectively from the start.
• Distributed systems experience: Hands-on experience building and operating distributed or event-driven architectures, including an understanding of failure modes, retries, consistency, idempotency, and service communication.
• AI-assisted software development: Demonstrated experience using AI coding tools to support substantial code migrations or modernization initiatives, such as framework upgrades, service rewrites, or programming lang…