AVP, AI (Data Science/Engineer) Remote - EST

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.

Strategic Analytics is a dynamic and growing team at Arch that drives innovation and transforms how the business operates. We build AI-first, agent-driven products that change how Arch underwrites, services, and learns from its book, combining frontier LLMs, multi-agent systems, retrieval-augmented generation (RAG), evaluation frameworks, and traditional machine learning. Our mission spans agentic automation, decision intelligence, AI-driven insights, and the responsible deployment of AI at scale. With a proven track record of productionizing dozens of high-quality GenAI products over the past three years, we are continuing to scale our impact and are seeking an AVP, AI Engineering to lead the design and application of advanced AI systems within Strategic Analytics.

Reporting to the SVP of AI & Automation, you will lead the development of multi-agent AI solutions that automate complex business decisions across underwriting and claims. This role is focused on applying AI, machine learning, and data science to solve high-value business problems, establish decision frameworks, and ensure AI systems deliver measurable outcomes with high levels of accuracy and trustworthiness.

Key Responsibilities

• Lead the design of multi-agent AI systems that coordinate specialized models and agents to solve complex business problems.

• Drive the end-to-end delivery of AI-powered underwriting and claims solutions from experimentation through production deployment.

• Develop and evaluate decision frameworks that combine LLMs, retrieval systems, machine learning models, business rules, and human review.

• Establish methodologies for measuring model performance, calibration, confidence, accuracy, and business impact to determine when automation is appropriate.

• Define the conditions under which AI-driven decisions should be trusted, reviewed, or escalated.

• Partner with cross-functional teams to integrate AI capabilities into business workflows and operational processes.

• Mentor data scientists, AI engineers, and analysts on agentic AI, model evaluation, prompt engineering, and responsible AI practices.

• Establish standards for AI evaluation, monitoring, governance, and continuous improvement within the AI & Automation Center of Excellence.

• Translate business opportunities into scalable AI solutions that deliver measurable business value.

Required Skills and Experience

• 7+ years of experience in AI, machine learning, data science, analytics, or related disciplines.

• 3+ years of people leadership experience.

• Demonstrated experience building and deploying production-grade AI, machine learning, or agentic systems beyond proof-of-concept work.

• Strong track record of developing supervised learning models (ML and/or GLMs) that have delivered measurable financial impact.

• Deep understanding of model evaluation, experimentation, statistical analysis, and decision science.

• Strong experience evaluating AI technologies, platforms, and vendors.

• Strong Python experience for data science, machine learning, and AI development.

• Exceptional problem-solving skills with the ability to frame ambiguous business challenges as analytical and AI opportunities.

• Strong communication skills with the ability to influence technical and non-technical stakeholders.

• Hands-on experience with modern AI technologies, including LLMs, RAG, agentic systems, evaluation frameworks, and emerging AI tooling.

Desired Skills and Experience

• Familiarity with P&C insurance, including underwriting, claims, or the submission lifecycle.

• Experience with retrieval-augmented generation (RAG), evaluation frameworks, and structured-output techniques.

• Experience applying AI and machine learning within enterprise environments.

• Experience leading multidisciplinary teams across data science, AI, analytics, and technology functions.

• Demonstrated commitment to staying current with advancements in AI through research, experimentation, publications, conference participation, or contributions to the AI community.

Education

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Analytics, or equivalent practical experience. 

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For individuals assigned or hired to work in the location(s) indicated below, the base salary range is provided. Range is as of the time of posting. Position is incentive eligible.

$185,000 - $235,000/year

• Total individual compensation (base salary, short & long-term incentives) offered will take into account a number of factors including but not limited to geographic location, scope & responsibilities of the role, qualifications, talent availability & specialization as well as business needs. The above pay range may be modified in the future.

• Arch is committed to helping employees succeed through our comprehensive benefits package that includes multiple medical plans plus dental, vision and prescription drug coverage; a competitive 401k with generous matching; PTO beginning at 20 days per year; up to 12 paid company holidays per year plus 2 paid days of Volunteer Time Offer; basic Life and AD&D Insurance as well as Short and Long-Term Disability; Paid Parental Leave of up to 10 weeks; Student Loan Assistance and Tuition Reimbursement, Backup Child and Elder Care; and more. Click here to learn more on available benefits.

Do you like solving complex business problems, working with talented colleagues and have an innovative mindset? Arch may be a great fit for you. If this job isn’t the right fit but you’re interested in working for Arch, create a job alert! Simply create an account and opt in to receive emails when we have job openings that meet your criteria. Join our talent community to share your preferences directly with Arch’s Talent Acquisition team.