AVP, Software Engineering Lead

The Hartford•Hartford, CT

10d•Hybrid

About The Position

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 AVP, Software Engineering Lead is a senior technology leader responsible for defining and executing engineering solutions with an AI-first mindset across the Corporate Functions IT organization. Reporting to the CIO of Corporate Functions, this role drives the re-imagination of software engineering, improving our software development lifecycle using AI-first processes, and ensuring AI‑driven capabilities are designed, built, and scaled safely, reliably, and in alignment with enterprise standards, governance, and risk. This role sets the roadmap for advanced software engineering teams to deliver AI‑enabled solutions, agent‑augmented workflows, and AI‑first engineering capabilities, partnering closely with Data & AI, Product, Architecture, Security, Risk, and Business leaders. The AVP will drive the modernization of engineering practices, accelerating delivery and productivity, while demonstrating measurable business value. This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office locations (Hartford CT, Charlotte, NC or Chicago IL) will have the expectation of working in an office 3 days a week. Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be authorized to work in the US without company sponsorship.

Requirements

15+ years of technology experience in software engineering, including 5+ years leading engineering teams.
Led AI centric software engineering transformations
Proven experience building software engineering practices, with a special focus on AI-first engineering.
Deep expertise in agentic AI concepts and architectures, including multi-agent systems and non-deterministic workflows.
Strong systems thinking and ability to operate across strategy, architecture, and execution.
Demonstrated success influencing distributed, and cross‑functional engineering teams.
Experience operating within regulated, risk‑sensitive environments (insurance or financial services strongly preferred).
Excellent communication skills with the ability to influence senior leaders across Technology, Data & AI, and the Business.
Bachelor’s degree in computer science, Engineering, Data Science, or related field (advanced degree preferred).
Expertise building and leveraging Agentic AI solutions in support of software engineering processes and reimagining the software lifecycle with an AI lens.
Expertise implementing modern software engineering practices, cloud‑native architectures, API‑driven and event‑based systems.
Strong background in CI/CD, DevSecOps, automation‑first delivery, and reliability engineering.
Familiarity with AI‑assisted development tools, AI platforms, and modern engineering accelerators.
Experience defining engineering standards, reference architecture, and platform reuse strategies.

Nice To Haves

advanced degree preferred

Responsibilities

Define and lead the AI engineering strategy aligned to enterprise technology, Data & AI, and business priorities.
Own end‑to‑end software engineering reimagination and rollout of AI-first tools and processes to our technology organization.
Ensure AI-first software solutions are engineered for security, resiliency, performance, cost efficiency, and operational sustainability.
Establish and evolve AI‑first engineering standards, patterns, and best practices, including GenAI and agent‑augmented development approaches.
Drive adoption of AI‑assisted development tooling and modern engineering accelerators to improve developer productivity and quality.
Partner with Architecture and Platform teams to define reusable AI engineering reference architectures, integration patterns, and guardrails.
Promote consistency and scale across AI implementations while enabling innovation and responsible experimentation.
Drive acceleration and efficiency using AI across software engineering teams, balancing speed, quality, risk, and cost.
Strengthen and champion AI-first SDLC, DevSecOps, CI/CD, and automation practices.
Ensure production readiness through robust testing, observability, monitoring, and incident response practices.
Use data‑driven insights to improve delivery predictability, flow efficiency, and engineering health.
Partner with Data & AI, Risk, Legal, Compliance, Cybersecurity, and Architecture teams to ensure AI engineering solutions meet enterprise governance and regulatory expectations.
Implement required engineering controls, including logging, auditability, model integration controls, and operational safeguards.
Ensure alignment with the Enterprise AI Operating Model, risk tiering, and approval processes.
Proactively identify and mitigate technology, security, and operational risks associated with AI‑enabled systems.
Elevate high‑performing software engineering teams with AI-first mindset.
Provide leadership, mentorship, and coaching to senior engineering talent.
Drive workforce strategy, succession planning, and capability uplift aligned to future‑ready AI and engineering skills.
Foster a culture of accountability, innovation, continuous improvement, and engineering excellence.