VP Head of Engineering

The Hartford•Hartford, CT

1d•Hybrid

About The Position

The Hartford is seeking a Head of Engineering within Actuarial to lead the next phase of digital transformation. This executive will drive innovation, operational excellence, and AI adoption across actuarial functions, ensuring the organization remains at the forefront of analytics, automation, and risk management. This role will be part of the Executive Leadership team for the Chief Actuary, leading three engineering teams. One team will focus on data management, establishing a strong data set foundation and implementing AI-driven data quality monitoring. The second team will create datasets and develop AI-powered tools for data consumption within the Actuarial organization, including advanced analytics dashboards. The third team will concentrate on piloting new proof-of-concepts (POCs) and executing short-term tactical builds that will transition into production by the other teams. This position will empower machine learning and artificial intelligence solutions, supporting deeper analytics for the Actuarial team across a wide range of strategic initiatives. The role involves collaboration with data scientists, data engineers, and actuaries in a highly collaborative development environment, driving AI transformation through joint innovated initiatives, cross-training on AI/Machine Learning methodologies, and fostering a culture of experimentation. Heavy interaction and training of partner-customers in actuarial will ensure successful AI adoption and maximize business impact. This is an exciting opportunity for a visionary leader to shape the future of data engineering and analytics within a dynamic and innovative insurance environment, driving strategic impact across pricing, profitability, and business transformation initiatives. This role will have a Hybrid work schedule, with the expectation of working in an office (Hartford, CT, Chicago, IL or Charlotte, NC) 3 days a week. Candidates must be eligible to work in the US without company sponsorship.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.
Minimum 15 years in data engineering or software engineering roles, with at least 5 years in leadership positions.
Direct experience building and operating data platforms, pipelines, and AI/ML solutions at scale.
Expertise in cloud platforms (Azure, AWS, GCP), big data technologies (Hadoop, Spark, NoSQL), data modeling, ETL/ELT, and modern software engineering practices.
Ability to credibly challenge technical decisions and guide architectural choices.
Proven ability to lead, mentor, and develop high-performing engineering teams.
Strong communication skills, with the ability to translate complex technical concepts for both technical and non-technical audiences.
Demonstrated success in setting technical vision, driving execution, and delivering measurable business outcomes.
Experience balancing long-term strategy with day-to-day operational needs.
Track record of driving transformation, challenging the status status quo, and implementing innovative solutions in complex environments.
Candidates must be eligible to work in the US without company sponsorship.

Nice To Haves

Advanced degrees preferred.
Experience working in insurance, financial services, or actuarial analytics is highly desirable.
Understanding of regulatory, reporting, and modeling requirements in these sectors.
Relevant cloud/data engineering certifications (e.g., AWS Certified Data Engineer, Azure Data Engineer Associate).
Executive education in AI, digital transformation, or insurance analytics.

Responsibilities

Define and articulate the technical strategy for data engineering and AI enablement, ensuring alignment with actuarial department objectives and broader business goals.
Champion modern engineering practices and drive the adoption of scalable, secure, and innovative data solutions.
Serve as the technical authority for the team, leveraging deep engineering experience to challenge assumptions, surface opportunities to improve approaches and suggest constructive alternatives, and guide the team toward best-in-class solutions.
Provide constructive feedback and foster a culture of accountability, rigor, and continuous improvement.
Oversee the design, development, and operation of actuarial data platforms, pipelines, and AI/ML solutions.
Ensure delivery of high-quality, production-ready systems that support advanced analytics, actuarial modeling, and business intelligence.
Implement and enforce data governance, security, and compliance standards.
Oversee data quality, lineage, and stewardship processes to ensure data is trustworthy and actionable for actuarial and business use.
Partner with actuarial, data science, IT, and business stakeholders to translate business needs into technical requirements and actionable engineering plans.
Advocate for engineering priorities at the executive level.
Monitor emerging technologies, tools, and methodologies in data engineering, AI, and insurance analytics.
Lead the evaluation and adoption of innovations that drive business value and operational excellence.
Mentor and develop engineering talent, fostering a high-performance, inclusive, and collaborative team environment.
Establish career pathways and training programs to elevate technical capability and leadership maturity.