Associate Data and AI Engineer at The Hartford in Chicago, IL

Summary: The Hartford is an insurance company committed to making a difference and helping others achieve their goals. As an Associate Data and AI Engineer, you will contribute to the Claims Data Science team by designing, developing, and implementing AI assets to enhance claim outcomes and improve customer experience. Responsibilities: - Implementing data pipelines that bring together structured, semi-structured and unstructured data to support Predictive, AI and Agentic solutions - Build and maintain scalable and robust AI-driven systems using technologies such as Snowflake, REST API’s, Apache Kafka, AWS Kinesis, Spark streaming, or similar - Collaborate with external partners such as Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams - Translate business requests into technical requirements for small and medium complexity engineering tasks - Validate internal and external data sources for availability and quality when asked. Work with SMEs to describe and understand data lineage and suitability for a use case - 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 teams if needed - Ensure the reliability, availability, and scalability of AI solutions and systems through effective monitoring, alerting, and incident management - Collaborate closely with AI Ops and infrastructure teams to ensure seamless deployment, operation, and maintenance of AI / ML systems Required Qualifications: - Bachelor's degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline - Experience developing solutions using Python and SQL, and using AI code assistants as part of daily workflow - Familiarity working with Github - Familiarity working in an Agile team - Exposure to data ingestion from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON - Exposure to ETL concepts, metadata management and data validation - Exposure to Automation tools (Autosys, Cron, Airflow, etc.) required - Exposure to GCP or AWS Services (i.e. S3, EMR, etc.) a plus - Exposure to Cloud Formation, Terraform, TeamCity, Jenkins, Octopus and other IAC tools and platform a plus - Exposure to Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus - Able to communicate effectively with both technical and non-technical teams - Able to translate complex technical topics into business solutions and strategies - Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position Required Skills: Python, SQL, GitHub, Agile methodology, Data ingestion, Relational databases, Hadoop, Spark, Cloud data sources, XML, JSON, ETL concepts, Metadata management, Data validation, Automation tools, Autosys, Cron, Airflow, GCP, AWS Services, Cloud Formation, Terraform, TeamCity, Jenkins, Octopus, Infrastructure as Code (IaC), Cloud data warehouses, Snowflake, Redshift, Data pipelines Benefits: Short-term or annual bonuses, Long-term incentives, On-the-spot recognition