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Software Engineer II – AI Agents & Harnesses

Job in Hartford, Hartford County, Connecticut, 06112, USA
Listing for: Travelers
Full Time position
Listed on 2026-09-09
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), DevOps, Full Stack Developer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 120000 - 199000 USD Yearly USD 120000.00 199000.00 YEAR
Job Description & How to Apply Below

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

$ - $

Target Openings

2

What Is the Opportunity?

What Is the Opportunity?

As a member of the Enterprise AI and Emerging Technology organization at Travelers, you’ll be joining a strategic and collaborative team focused on transforming our business and technology capabilities leveraging best in class AI-enabled technology. We’re looking for a Software Engineer II in the Enterprise AI Platforms organization to join our team focused on delivering the agent harnesses and platform capabilities that enable and accelerate the development of generative AI applications across the enterprise.

Will embed with partner teams to accelerate high-priority agentic delivery, moving to where the need is greatest and leaving those teams able to sustain the work. Engineers at this level work across the full architecture of product delivery from requirements gathering to maintenance and enhancement of existing systems.
Will lead solution design for assigned work streams, participate in stakeholder conversations, and build collective ownership across engineering, architecture, and product.
This role is for engineers who become productive quickly in unfamiliar codebases and who bring production-ready delivery experience to a fast-paced environment.

What Will You Do?
  • Design and deliver production-grade harness capabilities that engineering teams leverage to build and deploy generative AI applications.
  • Drive architecture and system design for agentic components across multiple teams, advancing the technical patterns and engineering standards adopted across the enterprise.
  • Help teams align to enterprise standards and practices in source code management, testing, CI/CD, and modern engineering principles.
  • Advance test automation and raise the quality bar on the harness and the systems it serves.
  • Apply systems thinking to identify and resolve the cross-team dependencies and bottlenecks that slow delivery down.
  • Mentor engineers inside and outside the team and contribute reusable capabilities rather than one-off solutions.
  • Engage directly in stakeholder conversations and translate technical direction into terms the business can act on.
  • Participate in cross-organizational engineering events and technical forums to share harness patterns and practices across the enterprise.
  • Perform other responsibilities as assigned.
What Will Our Ideal Candidate Have?
  • 4+ years of hands-on software development experience, including demonstrated production delivery of AI solutions you have supported at scale.
  • Proficiency in Python
    , with experience in additional languages such as Type Script , particularly for building AI integrations.
  • Hands-on experience building, deploying, and evaluating generative AI applications, including the runtime concerns around them: orchestration, tool interfaces, context and memory management, and guardrails.
  • Experience using agentic coding tools
    , with an informed point of view on where they help and where they fall short.
  • Hands-on experience across the cloud delivery stack: AWS and/or Azure, Kubernetes, infrastructure as code such as Terraform or CDK, and CI/CD tooling such as Git Hub Actions or Jenkins.
  • Hands-on experience designing, delivering, and maintaining large,…
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