Software Engineer II, Enterprise Agentic AI

Who Are We?

Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it.

Job Category

Technology

Compensation Overview

The annual base salary range provided for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. As part of our comprehensive compensation and benefits program, employees are also eligible for performance-based cash incentive awards.

Salary Range

$120,400.00 - $198,700.00

Target Openings

1

What Is the Opportunity?

Join the Enterprise AI and Emerging Technology organization at Travelers! This is an opportunity to be part of a dynamic team of engineers passionate about applying artificial intelligence to change the insurance industry.

Travelers is seeking a talented Software Engineer II to join our innovative team as we transform our Technology landscape. This role will be instrumental in establishing enterprise standards, architectural patterns, and foundational infrastructure to enable agentic AI systems to operate securely and effectively at scale. You'll design and build critical platforms including MCP (Model Context Protocol) servers, registries, gateway services, and orchestration frameworks that power AI-driven automation across our organization.

The ideal candidate brings expert-level Python programming skills with a proven track record of delivering enterprise-grade solutions to production. You should be experienced with cloud platforms (AWS or Azure), familiar with Kubernetes concepts, and passionate about emerging AI technologies. Knowledge of Model Context Protocol and generative AI is a strong plus. Working within an agile team, you'll tackle advanced end-to-end engineering challenges, from designing cloud-native architectures and developing AI integration layers to implementing infrastructure as code, testing agentic workflows, and establishing robust observability patterns for AI systems.

What Will You Do?

• Design and develop enterprise-grade infrastructure for agentic AI systems, including MCP registry and gateway services, MCP servers, and orchestration platforms that enable secure, scalable AI agent deployments
• Help define and implement architectural patterns and best practices for agentic AI integration across Travelers' technology landscape, serving as a technical advisor to product teams
• Build and maintain cloud-native solutions leveraging container orchestration
• Develop Python-based services and frameworks that facilitate AI agent communication, tool integration, and workflow management using MCP standards
• Establish observability, health monitoring, and alerting patterns specific to agentic AI systems, ensuring reliability and transparency in autonomous operations
• Provide technical guidance and mentorship to engineers adopting agentic AI patterns and contribute to internal knowledge bases and documentation
• Stay current with rapidly evolving generative AI technologies, agentic frameworks, and industry best practices, bringing innovative solutions to the team
• Work autonomously to analyze, assess, and resolve sophisticated defects and incidents, demonstrating strong problem-solving skills within our collaborative agile environment

What Will Our Ideal Candidate Have?

• Advanced proficiency in Python with experience using modern frameworks and best practices for building production-grade services and AI integrations
• Hands-on experience with cloud platforms, particularly AWS or Azure services and architecture in production environments
• Solid understanding of Kubernetes concepts and container orchestration patterns
• Knowledge of generative AI technologies, large language models (LLMs), and emerging agentic AI frameworks
• Familiarity with Model Context Protocol (MCP) for AI agent communication and tool integration (or enthusiasm to learn)
• Experience building APIs, microservices, and distributed systems with focus on reliability, security, and scalability
• Experience with Terraf