Jobs at The Hartford Financial Services Group, Inc.

Lead business data analysis and requirements gathering for enterprise data services. Perform data discovery, profiling, and SQL-based analysis; maintain data mapping and transformation rules; mentor analysts; liaise between business and IT; drive data quality fixes and process improvements within an Agile, hybrid team.

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.

Lead design and implementation of automated test frameworks and test data management, drive continuous testing with GenAI, mentor QA teams, collaborate across vendors and IT to improve test coverage, optimize execution times, support DevOps/release activities, perform defect analysis, and define quality engineering standards and metrics.

Lead design, development, and optimization of ETL/ELT pipelines and data products for telematics and third-party data. Ingest large-scale datasets into the enterprise data lake/lakehouse, implement CI/CD and DataOps practices, orchestration (MWAA/Autosys/Control-M), observability, and resilient self-healing pipelines. Mentor team members, collaborate with architects, data scientists, and BI teams, run POCs, and apply RAG and AI-driven systems while ensuring governance, security, performance, and data quality.

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.

Design and deliver AI-enabled solutions as a Staff Software Engineer, focusing on applications across HR and Law, ensuring robust integrations and cloud applications.

The Senior Staff Software Engineer will lead quality engineering efforts, design test automation frameworks, mentor teams, and ensure high-quality delivery across systems.

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

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.

The Account Manager facilitates insurance placements for small businesses, managing relationships with brokers, providing policy advice, and achieving sales goals.

Manage multinational network partner relationships and service delivery to meet KPIs. Lead stewardship meetings and in-person visits, handle escalations, support onboarding, maintain Global Online portal and mailbox, perform SLA reporting, assist with outbound reinsurance slips, premium reconciliation, and local policy quality control.

Lead the Personal Insurance modeling team, driving innovation in predictive modeling, machine learning, and actuarial analytics, while managing team performance and collaboration with cross-functional teams.

Lead alignment of Enterprise Data Services or Applied AI & Analytics portfolios with enterprise data/AI strategy. Oversee portfolio prioritization, IT budgeting, financial accountability, vendor management, and value-stream coordination. Partner with executive stakeholders to meet efficiency targets and manage annual portfolio spend (~$90M+). Promote Agile/DevOps/Scaled Agile practices and continuous improvement.

Lead strategy and execution for Employee Benefits data architecture, modernize data ecosystems using cloud and AI, design real-time pipelines, lakehouse and RAG/vector architectures, mentor data architecture teams, drive governance, developer productivity, and cross-functional alignment to enable analytics, AI, and compliant data products.

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.

Design, build, and operationalize production-grade ML and generative AI solutions and MLOps services. Collaborate with data, product, cloud, and architecture teams to deploy and monitor models in AWS and GCP. Implement CI/CD, IaC, workflow automation, and API services to ensure scalable, repeatable model deployments and observability.

Join an Agile Scrum team to define, scope, and certify domain-level data products (quote, policy, premium, loss). Perform end-to-end business/data analysis, stakeholder liaison, data stewardship, use GenAI and Big Data tools for mapping and profiling, ensure data quality and governance, and support delivery of analytics and the product (data asset) roadmap.

The Solution Architect designs end-to-end solutions for underwriting, driving innovation with emerging technologies, and ensuring compliance and security while collaborating across 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.

Lead design and implementation of AI-ready data platforms and scalable batch/streaming pipelines to support Generative AI and RAG solutions. Own architecture, reliability, governance, observability, and operationalization of production GenAI data systems across cloud environments. Mentor engineers and collaborate cross-functionally to integrate AI data products into enterprise workflows.