AVP, Applied AI and Engineering

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.

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

$173,700.00 - $286,600.00

1

AVP, Applied AI & Engineering is accountable for applying AI to how the Enterprise Digital, Data & Analytics (EDDA) organization plans, builds, tests and delivers its platforms, products, solutions and services and is accountable for measurably accelerating engineering productivity and quality across the development lifecycle.
The AVP leads a lean, hands-on engineering lab that re-engineers EDDA's delivery workflows, producing proven engineering patterns, code assets and practices that EDDA's teams adopt in their own delivery. Working in close partnership with EDDA leadership, the role drives adoption of AI engineering best practices, measures the productivity and savings it delivers, and runs a rotational program that brings engineering talent from across EDDA into the lab and returns them to their teams as AI-fluent practitioners.

What Will You Do?

• Leads a hands-on engineering lab that re-engineers EDDA's software and data delivery workflows with AI (e.g., data pipeline engineering, application development, testing, release and site reliability), proving each pattern end to end before it scales.
• Partners with enterprise groups to align EDDA priorities and work with broader direction, priorities and strong 2-way collaboration.

• Codifies the lab's work into reusable patterns, code assets, scripts and playbooks, and partners with EDDA’s teams to embed them in their delivery so efficiencies land in the teams that build and run EDDA's products rather than accumulating in one place.

• Develops AI-assisted engineering patterns for EDDA's SaaS and enterprise platforms such as Salesforce and Genesys, accelerating configuration, customization, extension and testing in partnership with the teams that own each platform.

• Owns the AI-Enabled SDLC experimentation agenda for EDDA, deciding which engineering use cases get tried, how results are judged, and what scales versus what stops, so investment decisions rest on evidence rather than advocacy.

• Owns AI-Enabled SDLC standards and engineering productivity practices across EDDA, using AI to transform requirements, architecture, coding, testing and DevSecOps, setting the practices that raise delivery throughput and quality within EDDA's teams.

• Sets the annual Applied AI agenda with EDDA leadership, selecting a focused set of high-value engineering use cases across data and digital and aligning them to team’s priorities, so the lab's work complements rather than duplicates delivery in flight.

• Redesigns EDDA's engineering workflows around AI and agents rather than automating steps inside existing processes, tying each pattern to a measurable outcome such as cycle time, throughput, quality or cost to deliver, so AI-Enabled SDLC savings are tracked and reported.

• Establishes and runs the rotational program that staffs the lab, partnering with data and digital team leads to release engineers into ring-fenced rotations with their own goals and OKRs, and with Learning & Development on a certification path, seeding AI capability across EDDA rather than concentrating it in one place

• Builds and fosters collaborative relationships with EDDA's teams and engineering leaders, with the ability to influence executive-level leadership on how EDDA applies AI to the way it engineers and delivers.

• Provides leadership, direction and execution focus to a lean Applied AI & Engineering team, leading with a diverse and inclusive mindset and engaging team members so they reach their full potential

• Manages technical resource allocation, partnering with the PMO on capacity planning across the rotational model and delivery and financial tracking, alongside on-boarding, performance management and offshore approach/structure.

• Partners with the PMO to run the operating cadence for the lab's work in flight (e.g., setting consistent success criteria, regular review, measurement against expected outcomes, and the escalation and decision-making protocols that keep stakeholders aware of status) with patterns handed to EDDA’s teams rather than retained as a standing portfolio.

• Perform other duties as assigned.

What Will Our Ideal Candidate Have?

• Ten years of related experience; including insurance / financial services industry experience.
• Demonstrated experience implementing current technology trends and techniques (e.g., cloud-based solutions leveraging microservices).
• Interprets internal/ external business challenges and recommends best practices to improve SDLC processes.
• Excellent delivery skills with the ability to examine and assess the effectiveness of software design strategies and methodologies, devise, apply, and share ways to ensure the quality of complex computer systems, incorporate awareness and understanding of work happening outside of the team, and develop widely used technical metrics that enable engineers to better understand and deliver their work.
• Demonstrated track record of domain expertise including the ability to consult on business priorities and optimize value by identifying business aligned solutions and improve company capabilities by thoughtfully introducing concepts and technologies from the industry.
• Strong problem solving skills with the ability to create architecture that is particularly robust against single points of failure and turn future areas of need into action.
• Excellent communication skills with the ability to describe technology concepts in ways the business can understand, document effectively, and collaborate across disparate groups.
• Strong leadership skills with the ability to engage with other leaders and networks to solve problems as well as work to improve the entire engineering organization by sharing knowledge while creating opportunities for others to develop skills.

What is a Must Have?

• Bachelor’s degree in computer science, related STEM field, or its equivalent in education and/or work experience.
• 8 additional years of software engineering experience.
• 3 years of technical leadership experience.