Jobs at The Hartford Financial Services Group, Inc.

Lead a small actuarial team supporting Middle & Large Property lines, owning loss ratio planning, catastrophe risk budgeting, monitoring loss and premium trends, supporting reinsurance, producing pricing and financial materials for leadership, and delivering ad hoc and emerging-risk analyses to improve portfolio performance.

Lead migration of an on-premises Oracle PL/SQL system to Snowflake on AWS, design data models and ETL processes, write complex SQL transformations, coordinate cross-functional teams, support legacy and new applications, document procedures, and mentor other data engineers.

Build and maintain scalable cloud-native ETL/ELT pipelines and data platforms to support analytics and ML. Implement IaC and CI/CD, enable MLOps, ensure data quality, monitoring, and collaborate with data scientists and product teams to deploy production AI services.

Place and retain small commercial insurance accounts through wholesale brokers, using product and market expertise. Review complex submissions, advise agents, secure pricing, drive sales and retention, manage pipelines, resolve service issues, and collaborate with underwriting and internal partners. Hybrid role with territory goals and compliance responsibilities.

Design, build, and operate enterprise AI/ML platform capabilities (AIOps/MLOps/LLMOps). Develop GenAI features, experiment with models and services, and architect end-to-end solutions. Collaborate with data, cloud, and business teams, drive engineering execution, promote best practices, and mentor engineers. Ensure platform reliability, monitoring, and scalable deployments across cloud environments.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

The Senior IT Engineer will lead full stack development projects focused on AWS, architecting APIs, mentoring junior engineers, and ensuring application performance and security.

Design and build production-scale data pipelines, orchestration, and integrations on GCP to enable metadata-driven governance, lineage, automation, and AI-enabled workflows. Implement secure, observable, cost-efficient cloud data solutions, embed governance into engineering workflows, and drive CI/CD, testing, monitoring, and platform engineering best practices.

Lead enterprise data platform engineering strategy and teams to build, modernize, and operate scalable, secure data platforms, analytics, AI-ready capabilities, and Third-Party Data enablement. Drive platform architecture, cloud modernization, integration, governance, observability, and operational excellence while partnering with stakeholders to deliver analytics, BI, and AI-enabling solutions and mentor engineering leaders across a global, matrixed organization.

Design, build, and operationalize production-grade AI/Machine Learning solutions and MLOps services. Deploy models and API services to AWS and GCP using CI/CD and IaC, implement workflow automation, monitor post-production performance, research generative/ML techniques, and mentor junior engineers while collaborating with cross-functional data, cloud, and architecture teams.

Lead Applied AI strategy and execution across Employee Benefits and Operations, overseeing ML, generative and agentic AI, RAG, and predictive analytics lifecycles. Drive governance, model risk management, evaluation, deployment, cross-LOB prioritization, talent architecture, and regulatory readiness to improve enrollment, billing, service, and operational efficiency.

The AVP Applied AI leads data science and AI capabilities at The Hartford, managing complex AI portfolios and ensuring delivery of business value through scalable models and AI-driven systems. Responsibilities include overseeing team performance, technical direction, AI governance, and alignment with business outcomes, along with collaboration across departments and continuous improvement initiatives.

Lead planning, forecasting, and performance analysis for P&C lines; partner with finance, actuarial, and business leaders to provide insights, govern models, automate processes, and prepare executive reporting. Drive assumptions for loss ratios, catastrophes, reinsurance analyses, and earnings prep while mentoring a team and implementing analytics and AI-enabled improvements.

Hands-on technical leader designing and building scalable, cloud-native claims applications on AWS. Architect and implement Generative/Agentic AI (LLMs, RAG, agents), mentor engineers, drive DevOps and IaC (Terraform), and collaborate with cross-functional teams to deliver secure, maintainable enterprise software.

Architect and build production-grade agentic AI systems and platforms using Google ADK, MCP, LangChain/LangGraph, and AlloyDB. Develop agent harnesses, RAG/GraphRAG pipelines, vector retrieval and memory stores, Terraform-based GCP infrastructure, CI/CD for model deployments, and enterprise security and governance for sessioned agent interactions.

Lead design and delivery of scalable, secure software across full stack and cloud. Collaborate with product and architecture teams, mentor engineers, drive best practices, integrate AI-assisted tools, and participate in the full SDLC to ensure system stability and performance.

Lead infrastructure resilience for cloud and SaaS systems by implementing observability, IaC, CI/CD automation, incident triage and self-healing. Build tooling, alerts, AI-driven anomaly detection and runbooks, partner with architecture and infrastructure teams to improve reliability, performance, and security.

Lead development and maintenance of workers' compensation pricing methodologies and tools. Update model parameters, drive pricing initiatives, collaborate with underwriting/product/data science/IT, provide profitability analyses, and support implementation to improve accuracy, segmentation, and profitable growth across business segments.

Senior technical leader responsible for the reliability, resilience, availability, and performance of enterprise data platforms and pipelines. Define RE strategy, SLO/SLI frameworks, observability, AIOps automation, and IaC/CI-CD standards. Lead cross-organizational initiatives, mentor engineers, and embed reliability into data product lifecycles across AWS/GCP, Snowflake, EMR/Hadoop/Spark, and container platforms.

Lead infrastructure resilience by implementing observability, IaC, automation, and AI-driven detection to ensure cloud and SaaS system stability. Drive tooling, alerts, self-healing, CI/CD optimization, incident triage/restore, and partner across architecture and engineering to improve performance, reliability, and cost efficiency.