AVP Applied AI

AVP Data Science - GD05AE Weu2019re 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 u2013 and to help others accomplish theirs, too. Join our team as we help shape the future. The Assistant Vice President (AVP), Applied AI leads data science, traditional machine learning, and agentic AI capabilities supporting The Hartfordu2019s Business Insurance. This role partners closely with underwriting, product, actuarial, and technology leaders to deliver scalable, production ready models and u2011AI drivenu2011 decision systems that support complex risks, bespoke products, and profitable growth across specialty markets. This role will have a Hybrid work schedule, with the expectation of working in an office (Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week. _Candidates must be eligible to work in the US without company sponsorship._ Primary Job Responsibilities Own delivery, performance, and risk outcomes for one or more large, complex Applied AI portfolios spanning multiple teams, domains, or lines of business. Translate enterprise and businessu2011unit AI priorities into multiu2011year portfolio roadmaps and investment plans. Ensure applied AI solutions deliver measurable business value while meeting standards for security, reliability, explainability, fairness, safety, and cost efficiency across solution types including generative and agentic AI, retrievalu2011augmented systems, forecasting, recommendation systems, anomaly or fraud detection, and multimodal use cases. Lead and develop Sr. Directors and Directors. Build leadership bench strength through succession planning, coaching, and capability development. Ensure consistent application of the Applied AI operating model, decision rights, delivery discipline, and escalation paths across the portfolio. Reinforce shared expectations for quality, evaluation rigor, and production readiness. Provide portfoliou2011level technical direction and rigorous oversight, partnering closely with Principal ICs, Architecture, AI Platform, and Centers of Excellence. Ensure consistent adoption of approved AI standards, patterns, and guardrails. Review and thoughtfully evaluate portfoliou2011level architectural choices, evaluation approaches, production readiness, and operational risk signals, guiding leaders through disciplined tradeu2011offs across quality, grounding, latency, cost, scalability, and regulatory risk. Accountable for consistent application of evaluation and monitoring practices across the portfolio. Ensure evaluation frameworks span classification, information retrieval, RAG/chat, forecasting, and customer or operational KPIs. Oversee governance of metric taxonomies, thresholds, validation evidence, gold and synthetic test sets, A/B testing practices, drift detection, failureu2011mode analysis, and incident response expectations. Ensure evaluation results inform prioritization, release decisions, and risk management at the executive level. Set portfoliou2011level expectations and governance for unstructured data and retrieval practices, including document ingestion pipelines, parsing, OCR, layoutu2011aware extraction, metadata and lineage management, access controls, PII detection and redaction, and auditability. Ensure retrieval strategy decisions, including embedding approaches, hybrid and dense retrieval patterns, reranking, grounding validation, and multilingual considerations, align with enterprise standards and regulatory requirements. Accountable for portfolio-level AI governance ensuring alignment with Legal, Compliance, Model Risk, Privacy, Security, and Audit partners. Maintain readiness for audits and regulatory review by ensuring governance artifacts, controls, escalation paths, and operational evidence are consistently established and enforced. Escalate material risks, tradeu2011offs, and investment decisions to VPs with clear options and implications. Partner with senior leaders across Product, Technology, Operations, Claims, Underwriting, Finance, and HR to align Applied AI delivery with business outcomes. Influence portfolio funding, prioritization, and workforce planning through evidenceu2011based assessments of delivery performance, evaluation outcomes, and risk considerations. Oversee portfoliou2011level planning, dependencies, resourcing, and financial stewardship. Adjust plans to address shifting priorities, capacity constraints, emerging technical risks, or regulatory changes. Drive continuous improvement in delivery effectiveness, operational resilience, governance maturity, and value realization across the Applied AI portfolio. Skills Demonstrated experience leading large, complex Applied AI portfolios in regulated enterprise environments. Proven ability to lead Sr. Directors and Directors, building durable leadership capacity and consistent operating discipline across organizations. Strong technical and regulatory fluency across applied AI, including generative and agentic AI, retrievalu2011augmented systems, evaluation and monitoring practices, and production AI operations, sufficient to review, inform, and govern senioru2011level decisions. Applied understanding of unstructured data and retrieval approaches, including document ingestion pipelines, OCR, layoutu2011aware extraction, embeddings, hybrid and dense retrieval, reranking, metadata and lineage management, and PII controls. Deep familiarity with AI governance, model risk management, responsible AI practices, and complianceu2011byu2011design expectations. Demonstrated success translating strategy into coordinated execution and investment decisions across multiple teams over multiu2011year horizons. Ability to influence VPs and senior partners through clear, datau2011driven communication of technical tradeu2011offs, evaluation outcomes, portfolio risks, and business impact. Education, Experience, Certifications and Licenses 12+ years of applicable experience with a Bacheloru2019s degree; fewer years may be accepted with a higher degree. Masteru2019s or Ph.D. preferred in Machine Learning, Applied Mathematics, Data Science, Computer Science, or a similar analytical field, or progress towards a relevant professional designation. 7u201310+ years leading leaders, large portfolios, or complex programs. Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartfordu2019s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $182,400 - $273,600 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

Created: 2026-04-22