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AVP, Software Engineering Lead

Remote / Online - Candidates ideally in
Hartford, Hartford County, Connecticut, 06112, USA
Listing for: The Hartford
Full Time, Part Time, Remote/Work from Home position
Listed on 2026-05-30
Job specializations:
  • Engineering
    AI Engineer (Applied/Software), Systems Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 182000 - 273000 USD Yearly USD 182000.00 273000.00 YEAR
Job Description & How to Apply Below

AVP Software Engineering – IE05FE

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 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.

Key Responsibilities
  • AI-first Software Engineering Strategy & Execution – 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.
  • AI‑First Engineering & Platform Enablement – 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.
  • Delivery, Quality & Operational Excellence – Drive acceleration and efficiency using AI across software engineering teams, balancing speed, quality, risk, and cost. Strengthen and champion AI-first SDLC, Dev Sec Ops , 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.
  • Governance, Risk & Controls – 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.
  • Talent Leadership & Engineering Culture – 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.
Required Qualifications
  • 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…
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