The Hartford

Data Engineer

• Participate in developing high quality, scalable software modules for next generation analytics solution suite
• Engage in activities with cross-functional IT unit stakeholders (e.g., database, operations, technical support, etc.)
• Formulates logical statements of business problems and devises, tests and implements efficient, cost-effective application program solutions
• Identify and validate internal and external data sources for availability and quality
• Work with SMEs to describe and understand data lineage and suitability for a use case
• Create data assets and build data pipelines that align to modern software development principles for further analytical consumption
• Perform data analysis to ensure quality of data assets
• Perform preliminary exploratory analysis to evaluate nulls, duplicates and other issues with data sources
• Assist in developing code that enables real-time modeling solutions to be ingested into front-end systems
• Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other data science teams

Full-stack Engineer

• Adopt, evolve, and govern the Quality Engineering strategy, standards, and operating model and adopt contemporary technology to ensure consistent, scalable, and high-quality delivery.
• Design, implement, and maintain robust automated test frameworks across applications, enabling reliable and repeatable validation of complex systems.
• Drive test automation through hands-on creation of automated test cases, test data management, review of automation delivered by teams, and resolution of complex automation challenges adhering to software engineering best practices.
• Proven ability to track, and leverage Quality and Quality Execution metrics to drive measurable improvements such as defect reduction and defect leakage prevention.
• Demonstrated track record of testing and quality execution within Agile and Scaled Agile frameworks, including sprint-level testing, end-to-end validation, and regression, performance, security and accessibility for external facing digital applications.
• Diagnose and resolve complex defects across distributed systems and third-party integrations.
• Improve system testability, observability, and reliability through direct code contributions and collaboration on system and application design.
• Facilitate and manage end to end quality execution, ensuring business capabilities are delivered with high quality from ideation through production.
• Mentor Quality Engineers with best practices, automation patterns, and scalable test design approaches.
• Proficient with DevOps tools and ability to participate in production release planning, execution.
• Drive the adoption and effective use of AI and GenAI tools to improve testing efficiency, effectiveness, and overall engineering productivity.

Senior Software Engineer – Quality

Underwriter

• Join our team as we help shape the future.
• You'll be on a team known throughout the industry for providing our customers with just the right amount of coverage.
• Your underwriting career means collaboration, inclusivity, innovative thinking and so much more.
• You'll put your creative insights to work with other underwriters and leaders, having a seat at the table with key decision makers.
• Opportunities for your career to grow in whatever direction you choose.

Underwriting Director, Ocean Cargo

Learning and Development

• Develop critical leadership and functional skills in areas such as IT Engineering, Application Development, Cyber Security, Data Analytics, Agile, DevOps, Digital Adoption, Project Management, and Process/Business Analysis.
• Participate in rotation assignments throughout the two-year talent development program.

Associate – Tech, Data, Analytics, Cyber, and Operations Leadership Development Program

Compliance

• Serve as Compliance Lead and single point of contact for states and accountabilities related to Personal Insurance across products, functions, and business units
• May also support P&C Data Calls and regulatory inquiries
• Effectively communicate with a wide range of business clients, including senior leaders
• Manage strategic initiatives and compliance issues; identify potential regulatory issues in business initiatives; offer thoughtful, creative solutions that are appropriate for the level of risk involved
• Direct and manage regulatory matters in a manner that builds confidence within the regulatory community and protects The Hartford
• Develop and execute compliance audit programs to proactively identify organizational vulnerabilities and develop strategies for ensuring future compliance
• Analyze regulatory requirements; provide business clients with practical and actionable advice

Compliance Assistant Director

Actuary

• Pricing support for PI Home rate indications that project rate needed to achieve a 15% return on equity
• Conducting comprehensive analyses using both internal and external data sources
• Evaluating loss development factors, forecasting loss and premium trends, and assessing current and projected expense ratios, among other key elements
• Additional support for Trend analysis to inform business decisions across multiple teams within Personal Insurance
• Understanding of modeling done by ERM for CATs and Risk and Profitability for BMP to use results in indications work noted above
• Develop and analyze internal and external monitoring reports serving as leading indicators to possible changes in rate indications
• Present findings and recommendations to teammates and business partners to guide future decisions

Actuarial Personal Insurance Reserving

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 deployment design, development and maintenance of both traditional ML and AI models.
• 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, Applied AI, 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

• 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.
• Accountable for deployment design, development and maintenance of both traditional ML and AI models.
• Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams
• Delivery of critical milestones for model deployment in the AWS and GCP cloud environments.
• Adopt and promote MLOps best practices to the Data Science community.

AI Machine Learning Engineer

Data Analyst

• Join a fast-paced and talented Agile Scrum team to unlock Data Capabilities for The Hartford’s Personal Insurance Business.
• Participate in the entire software development lifecycle process in support of continuous DATA delivery.
• Proactively manage the end-to-end analysis delivery and execution.
• Certify the analysis deliveries for development working within the Scrum Team enabling optimal data quality output.
• Function as liaison, consultant between various business functions impacting organization and leadership.
• Structure and drive working and informational sessions that promote collaboration and achieve desired outcomes for assigned business initiatives.
• Clearly give and receive information, requirements and specifications through verbal, written and presentation communication methods.
• Perform planning, monitoring and end-to-end Business/IT stakeholder management!

Business Data Analyst

Customer Support

• Demonstrating core knowledge and ability to process routine internal and external customer-initiated claim transactions to completion referring to the appropriate resource
• Utilizing claim systems and equipment to correctly process incoming and outgoing correspondence
• Assigning or reassigning claim tasks or customer transactions to appropriate party
• Creating or updating professional correspondence including appropriate documentation within claim files
• Handling inbound and outbound calls professionally and with empathy to respond to customers’ needs
• Managing daily workload and productivity goals to ensure tasks are completed timely and accurately
• Communicating clearly and concisely to effectively convey information

Claims Operations Support Specialist

Product Specialist

• Lead the design, development, and enhancement of complex insurance products
• Translate business needs into product solutions by partnering with Actuarial, Underwriting, Legal, Claims, and IT
• Ensure all products meet regulatory, compliance, and quality standards
• Deliver high-quality product updates with speed and precision
• Coordinate stakeholders across the organization to drive alignment, execution, and successful product delivery
• Utilize market insights, industry trends, and competitor analysis to support business segment strategies
• Serve as a key liaison between product and internal partners
• Act as the primary technical resource and subject matter expert for Product Specialists

Senior Product Specialist, Casualty

Director

• Accountable for end-to-end technology execution, quality, financials, and workforce management for strategic investments and maintenance, ensuring compliance with NFR (Compliance, Audit, SOX controls, Disaster Recovery).
• Partner with VSO, VSL, Business Transformation Leads and Agile product management teams to drive business value and prioritize capabilities.
• Responsible for delivery of Submissions Intake, Extraction and Ingestion.
• Manage and negotiate complex stakeholder relationships within and across Value Streams and business leadership.
• Develop and implement technology strategy, process improvements, risk mitigation, financial management, and resource planning.
• Collaborate with enterprise leaders on digital transformation, cloud migration, and Generative AI initiatives.
• Develop and partner with a large organization with strong workforce strategies, including providing direction for Release Train Engineers, Scrum Masters, Quality Analysts.
• Effectively manage multiple vendor partnerships in an onshore/offshore environment.
• Mature DevOps, RE, and QE practices, improve automation for continuous delivery, and build high-performing teams focused on continuous improvement.
• Oversee financial management, including cost and time estimation to deliver business value.
• Drive community engagement and productivity, lead innovation, implement new technologies, and demonstrate strong business acumen.
• Engage leaders to support technology changes, act as a trusted advisor to the leadership teams, and utilize strong analytical skills to influence decisions.

Director, IT Delivery – IDP Platform

• Lead the implementation of AI data pipelines integrating structured, semi-structured, and unstructured data to support AI and agentic solutions
• Develop AI-driven data systems that enhance data capabilities while ensuring adherence to industry best practices
• Implement and optimize Retrieval-Augmented Generation (RAG) architectures and integrate them with enterprise data platforms
• Design, build, and optimize scalable batch and streaming data pipelines with a focus on performance, resiliency, and operational efficiency
• Develop and maintain real-time data streaming pipelines using technologies such as Snowpipe
• Develop data domains and data products to support reporting, analytics, AI/ML, and data science use cases
• Ensure the reliability, availability, and scalability of data pipelines through monitoring, alerting, and incident management
• Implement reliability engineering best practices, including fault tolerance, redundancy, and disaster recovery
• Drive engineering discipline across data platforms, including observability, data quality, lineage, and governance
• Collaborate with DevOps and infrastructure teams to enable seamless deployment and operation of data systems
• Provide architectural leadership in partnership with Data Architects, including defining technical standards and influencing enterprise-wide practices
• Develop and integrate graph database solutions to support complex data relationships within AI systems
• Apply GenAI approaches to insurance-specific data use cases and challenges
• Lead the development of AI-ready data foundations that support scalable, production-grade solutions
• Ensure data platforms remain resilient, governed, and cost-efficient, aligned with enterprise cloud and data strategies
• Mentor junior engineers and contribute to communities of practice, promoting best practices, reusable patterns, and engineering standards
• Stay current with advancements in GenAI and apply relevant technologies and methodologies to platform evolution.

Senior Staff AI Data Engineer

DevOps Engineer

• Serve as technical liaison between AI COE and Platform Engineering & Enterprise SRE teams
• Ensure AI systems meet requirements for performance, latency, throughput, resiliency, recovery, observability and reliability
• Partner with AI engineers, Applied AI Scientist, and AI Architects to design, build and maintain scalable, fault tolerant AI systems as per SLO
• Partner with Platform engineering team to design and implement CICD, GITOps, and IAC (Terraform) modules
• Making sure we use our AgentOps NSA, standards, Ref. architecture and tooling
• Partner with enterprise release management and AI Governance team to build & deploy AI solutions using their platform tooling
• Supporting entire AI lifecycle as per the standard work template
• Build standardized deployment templates, reference architecture, automation scripts, terraform modules, CICD pipelines, and operational runbooks for AI workloads
• Design and build IDP (Harness) catalogs, templates & pipelines partnering with enterprise platform engineering team
• Manage production systems to ensure our enterprise SLOs are met
• Manage incident response for production systems, including triaging, escalating, RCA and implementing corrective actions

Principal AI Engineer – Agent Ops, SRE

• Design, develop, and maintain scalable and secure APIs
• Build and enhance Angular components and other front-end technologies
• Conduct code reviews and maintain quality standards for API and UI modules across multiple scrum teams within their Agile Release Train (ART)
• Adhere to architectural standards and maintain application integrity in collaboration with architects and technical leads
• Design solutions with a clear understanding of technology trade-offs, balancing risks and rewards to deliver optimal customer value
• Implement cloud-native architecture patterns that are scalable, reusable, secure, and cost-efficient, including multi-region support, fault tolerance, and data replication strategies
• Utilize AWS services for application development and deployment, including (but not limited to): Lambda, CloudWatch, ECS, EKS, RDS, S3, IAM, SNS, SQS, EventBridge, AWS Batch, AWS Directory, and Service Catalog
• Apply DevOps practices and leverage CI/CD tools for continuous integration and delivery
• Communicating risks, mitigations, and business impacts clearly and professionally, both verbally and in writing
• Present innovative ideas to leadership and identify opportunities for improvement
• Serve as the technical subject matter expert for billing applications and integration components
• Share knowledge and mentor team members (including sourcing partners) on development guidelines and best practices
• Demonstrate strong attention to detail and effectively manage multiple priorities in a fast-paced environment
• Take ownership and drive innovation to leverage technology for solving customer problems
• Oversee development teams by removing technical blockers and guiding architecture and design
• Maintain regular contact with other TLs for efficient progress across development streams
• Coordinate with other projects to support parallel development and reduce code or environment conflicts