The Hartford

Risk

• Conduct risk assessments, site surveys, and deliver actionable recommendations to reduce loss exposure with focus on customer-centricity and our service model to form partnerships while mitigating risk.
• Collaborate with underwriting, claims, and customers to develop tailored risk improvement strategies. Working with our distribution partners to help differentiate The Hartford in the marketplace.
• Leverage data analytics and digital tools to provide insights and predictive solutions.
• Serve as a trusted advisor, educating clients on emerging risks and best practices.
• Contribute to innovation initiatives that integrate AI and human expertise for precision and speed.

Risk Engineer – All Levels, Specialty Areas

Attorney

• Engage in cutting‑edge work at the intersection of artificial intelligence, privacy law and insurance operations
• Interpret AI and data breach notification laws
• Respond to data incidents involving potential exposure of personal information
• Lead investigation to identify root causes of incidents and legal reporting obligations
• Collaborate with cross-functional teams and stakeholders on AI and data incident response matters

AI and Privacy Legal Consultant

Data Scientist

• Design and prototype machine learning models for image and video data, with a focus on insurance-relevant use cases.
• Evaluate emerging technologies and vendors, providing technical assessments and recommendations.
• Collaborate with business stakeholders to identify high-impact opportunities for AI innovation.
• Translate ambiguous problems into structured experiments and communicate findings clearly.
• Partner with engineering and data science teams to transition successful prototypes into production-ready solutions.
• Stay current on the latest research and trends in AI, computer vision, and generative models.
• Mentor junior team members and contribute to a culture of curiosity and continuous learning.

Senior Data Scientist, Emerging Technology and Innovation

Data Engineer

• Contribute to the development of data pipelines, APIs, and services supporting AI and analytics platforms
• Assist in building and maintaining cloud-based data workflows for structured and unstructured data
• Write clean, well-documented, and testable code following established standards
• Support AI platforms such as: Synthetic data generation components (Deep Synthetic Foundry)
• Implement clearly defined features or enhancements under guidance from senior engineers
• Work with SQL and cloud data platforms (e.g., Snowflake) to ingest, transform, and validate data
• Ensure data quality, reliability, and performance in production pipelines
• Partner with Data Scientists, Engineers, and Product team members on shared goals

Junior Developer – Data Engineer, AI Platforms

DevOps Engineer

• Responsible for building reliability engineering and automation capabilities across the Claims, Contact Center & Digital Enablement portfolio
• Accountable for RE, DevSecOps and AIOps automation capabilities leveraging the necessary tools to enable our vision of CI/CD
• Build tools and capabilities needed by our cloud engineering teams to optimize development
• Provide support for the cloud transformation, adoption, and maturity of reliability engineering within their teams
• Develop and maintain a sustainable organization through the hiring, performance management, coaching and development of a multi-discipline organization

AVP Reliability Engineering

• Manage Cloud Engineers and Reliability Engineers
• Manage projects and plan future work
• Identify, drive and lead in the implementation of products and reference implementations to standardize how we deploy applications in AWS and GCP
• Designs reusable architectures and services that can be leveraged by agile teams to improve development velocity
• Knows how applications should be engineered by following fault tolerate best practices
• Develops applications in Python to support automating manual processes and repeatable decision making
• Develops Infrastructure as Code (IaC) using Terraform and CloudFormation templates, YAML files, build specifications, and Python Lambda functions
• Mentor Cloud Engineers and Software Engineers
• Troubleshoot problems with software and infrastructure

Manager, Reliability Engineer

Machine Learning Engineer

• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
• Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
• Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
• Accountable for design, development and maintenance of Models as Service.
• Work with junior engineers and peers to provide mentorship and thought leadership.
• Be comfortable presenting new concepts to technical audiences.
• Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams.
• Delivery of critical milestones for model deployment in the AWS and GCP clouds.
• Adopt and promote MLOps best practices to the Data Science community.

Senior AI, Machine Learning Engineer

Financial Planning and Analysis

• Partner with business leaders and support functions (HR, Transformation Office) to develop and maintain rolling 3‑year expense forecasts.
• Provide financial guidance and analytical support to influence decision-making and support achievement of operating objectives.
• Develop and maintain expense KPIs and staffing models across Global Specialty lines of business.
• Analyze monthly, quarterly, and year-to-date financial results, including variance analysis versus Budget and Prior Year; identify trends, risks, and opportunities.
• Support the preparation and review of consolidated Global Specialty reporting deliverables, including executive packages (e.g., Green Book and Blue Book).
• Drive continuous improvement in forecasting, metrics, and management reporting: advancing automation and enabling more predictive and prescriptive analytics.
• Build strong relationships across Finance and Global Specialty; recommend solutions and contribute to strategy development and execution.
• Perform ad hoc analyses and special projects in support of the CFO, business leaders, and senior management.

Assistant Director – Senior Financial Analyst, Global Specialty FP&A

Insurance

• Providing comprehensive insurance solutions
• Evaluating risk
• Confidently asking for the sale while overcoming objections
• Handling an average of 30-40 inbound calls per day

Inbound Sales Insurance Agent

Full-stack Engineer

• Design, develop, test, and maintain scalable backend services supporting intelligent document processing workflows.
• Build cloud-native applications on AWS, leveraging managed services to deliver secure, resilient, and highly available systems.
• Develop and optimize automated document workflows, including ingestion, classification, extraction, and validation pipelines.
• Own service-level concerns including performance, reliability, observability, and cost efficiency.
• Implement monitoring, logging, alerting, and fault-tolerant patterns.
• Collaborate with cross-functional partners to translate business needs into well-architected software solutions.
• Participate in system design discussions, code reviews, and technical decision-making.
• Contribute to CI/CD pipelines and infrastructure-as-code.
• Author and maintain technical documentation and runbooks.
• Evaluate emerging technologies and contribute to roadmap discussions.

Senior Cloud Software Engineer – Intelligent Document Processing

Administrative Assistant

• Provide advanced administrative support to Small Business Underwriting leaders (Director–VP level) and their teams
• Manage complex calendars and scheduling for assigned leaders, anticipating conflicts and prioritizing business-critical meetings
• Coordinate domestic travel arrangements and prepare accurate, timely expense reports in accordance with company policy
• Monitor and manage leader communications as requested, including acting on behalf of leaders when appropriate
• Serve as a proxy for supported leaders in enterprise systems (e.g., Workday, expense and travel tools, procurement systems)
• Maintain a high degree of confidentiality and sound judgment at all times
• Support onboarding, offboarding, and employee data accuracy
• Coordinate reports, track deadlines, and support ad-hoc analysis for leaders as needed
• Assist with departmental training logistics, new hire onboarding, and space or equipment coordination
• Act as a liaison with compliance, finance, legal, and other partners when planning events
• Ensure professional execution of events and visits, including VIP and leadership engagements

Senior Administrative Assistant, Small Business Underwriting

Software Engineer

• Act as a strategic risk advisor, partnering with clients to proactively identify emerging risks and cocreate practical, value-added mitigation solutions
• Demonstrate customer centricity and empathy by tailoring recommendations to each client’s industry, risk profile, and business priorities
• Conduct risk assessments and consultations across multi lines of insurance using onsite, hybrid, and virtual/digital delivery models
• Develop and execute data driven service plans that address loss drivers, operational exposures, and client business objectives
• Translate complex technical findings into clear, compelling insights using storytelling with data for clients, agents, and underwriting partners
• Leverage digital tools, analytics, and emerging technologies (e.g., dashboards, virtual tools, AI enabled insights) to enhance service quality, efficiency, and customer experience
• Collaborate cross functionally with underwriting, claims, sales, data, and technical experts to deliver integrated risk solutions
• Identify opportunities to expand Risk Services offerings and support profitable growth
• Engage in continuous learning to stay current on industry trends, emerging risks, and evolving technologies
• Mentor, coach, and support less experienced risk engineering consultants as appropriate by role level

Senior Field Risk Engineering Consultant

Director

• Set and execute a clear vision for enrollment growth enabled by technology across market segments
• Identify, evaluate, and recommend buy/build/vendor solutions to support enrollment effectiveness, scalability, and straight-through processing
• Establish a forward-looking enrollment technology roadmap aligned to business strategy, customer needs, and premium growth objectives
• Monitor performance against growth, customer satisfaction, and operational KPIs to inform investment and prioritization decisions
• Oversee the evolution of enrollment-related sales positioning, value propositions, and go-to-market messaging
• Lead enrollment components of pre-sale responses, including customer RFPs, finalist presentations, and solution design
• Partner with Sales and Underwriting to ensure enrollment capabilities are clearly articulated, differentiated, and aligned to customer needs and pricing strategies
• Support field teams with tools, insights, and guidance to improve close rates and enrollment outcomes
• Develop deep expertise in how benefits administration partners deliver the enrollment experience, including platform capabilities, limitations, and emerging enhancements
• Guide teams in advising customers on how to best leverage benadmin partners to maximize employee engagement, participation, and satisfaction
• Collaborate with external partners and internal stakeholders to influence roadmap alignment and integration opportunities
• Lead the design and evolution of Priority Business’s THPB enrollment materials platform and related straight-through-processing workflows
• Partner with Technology, Operations, and Product teams to ensure solutions are scalable, compliant, and operationally sound
• Ensure enrollment materials and execution processes are efficient, accurate, and aligned to customer and regulatory requirements
• Own ongoing assessment, selection, and management of enrollment-related technology vendors and tools
• Establish governance standards for enrollment technology usage, integration, and performance
• Identify opportunities to retire, enhance, or consolidate tools to reduce complexity and improve outcomes
• Lead, coach, and develop a team of enrollment and technology-focused professionals
• Influence across a highly matrixed environment, partnering with Sales, Relationship Management, Technology, Operations, Legal, and Marketing
• Drive change management and adoption for new enrollment capabilities across internal teams and customers.

Director, Enrollment Strategy – Technology

Learning and Development

• Lead strategic learning initiatives in partnership with business leaders
• Integrate instructional design, change management, and learning analytics to create programs
• Manage performance support content and facilitate cross-functional initiatives
• Align learning solutions with business priorities and key performance indicators (KPIs)

Senior Instructional Designer – Success Enablement Group

• Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices
• Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure
• Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions
• Stay up to date with industry advancements in AI and apply modern technologies and methodologies to our systems
• Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as GCP, Vertex AI, S3, AWS Bedrock, Spark streaming, or similar
• Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc
• Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management
• Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies
• Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems
• Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns
• Apply AI solutions to insurance-specific data use cases and challenges
• Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.