AVP Applied AI, Claims

## AVP Applied AI, Claims Apply locations:
Hartford, CT:
Columbus, OH:
Charlotte, NC:
Chicago, ILtime type:
Full time posted on:
Posted Todayjob requisition :
R2625510

AVP Data Science - GD05AE
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 Hartford is hiring an AVP leading Applied AI for the Claims organization. This leader will play a pivotal role in transforming the end-to-end Claims process by developing and embedding AI capabilities to enhance outcomes, process and experience.

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, 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 a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams; translate Claims and enterprise AI priorities into a multi-year roadmap and investment plan.
* Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions (e.g., forecasting, triage, recommendations, anomaly/fraud detection, RAG/assistants, and agentic workflow orchestration).
* Be the senior business partner for Claims leaders: proactively understand short- and long-term goals, shape the problem statements, define success measures, and ensure solutions are adopted and embedded into core claim processes and colleague experiences.
* Build deep partnerships within portfolio and value stream frameworks; promote agile, iterative delivery through cross-functional teams to ensure fit-for-purpose solutions and rapid learning cycles.
* Lead and develop senior leaders and teams (e.g., asset owners, data engineers, data scientists, ML engineers), building bench strength through succession planning, coaching, and capability development while creating an engaged and inclusive culture
* Provide portfolio-level technical direction and oversight, partnering with Principal Individual Contributors, Architecture, AI Platform, and Centers of Excellence to drive consistent adoption of approved standards, patterns, and guardrails
* Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk—especially for GenAI and agentic solutions operating in claims environments.
* Establish and enforce evaluation, monitoring, and production readiness across solution types (classification, regression, retrieval/RAG/chat, forecasting), including metric taxonomies, thresholds, validation evidence, gold/synthetic test sets, A/B testing, drift detection, failure mode analysis, and incident response expectations.
* Set governance expectations for unstructured data and retrieval across Claims (document ingestion, parsing/OCR, layout-aware extraction, metadata/lineage, access controls, PII detection/redaction, auditability), including embedding/retrieval strategies and grounding validation aligned to enterprise standards.
* Accountable for AI governance and compliance-by-design across the Claims portfolio, partnering with Legal, Compliance, Model Risk, Privacy, Security, and Audit; maintain audit readiness with clear controls, artifacts, escalation paths, and operational evidence.
* Influence technology integration and platform strategy by partnering with Technology, Data, AI Platform, AI/MLOps, and Architecture teams on tooling, standard work, reusable capabilities, and scalable patterns for Predictive, Generative, and Agentic AI.
* Champion reuse and scalability by partnering with AI platform owners and peers to develop and integrate reusable Claims AI capabilities within The Hartford’s AI platform.
* Provide thought leadership and change leadership: educate stakeholders, identify new AI opportunities, advance a data-driven culture, and drive change to…