The Hartford
Overview
Sr Staff AI Data Engineer
role at
The Hartford . Sr AI Data Engineer is responsible for implementing AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready. Location & Schedule
Hybrid work schedule with in-office expectation 3 days per week (Tuesday through Thursday). Offices may include Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC. Responsibilities
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 Apache Kafka, AWS Kinesis, 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 reusable patterns. Develop graph database solutions for complex data relationships supporting AI systems. 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. Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. 8+ years of data engineering experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark, Datamesh, Datalake or Data Fabric. 3+ years of AI/ML experience, with 1+ years of data engineering experience focused on supporting Generative AI technologies. Strong hands-on experience implementing production ready enterprise grade AI data solutions. Experience with prompt engineering techniques for large language models. Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models. Experience of vector databases and graph databases, including implementation and optimization. Experience in processing and leveraging unstructured data for AI applications. Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph). Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow. Experience with building AI pipelines that bring together structured, semi-structured and unstructured data including extraction, chunking, embedding and grounding strategies, semantic modeling, and preparing data for models and agentic solutions. Experience in vector databases, graph databases, NoSQL, Document DBs (e.g., AWS OpenSearch, Neo4j, MongoDB, DynamoDB). Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform. Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Strong written and verbal communication skills and ability to explain technical concepts to various stakeholders. Experience in multi-cloud hybrid AI solutions. AI Certifications; experience in P&C or Employee Benefits industry. Knowledge of natural language processing (NLP) and computer vision technologies; contributions to open-source AI projects or research in Generative AI are a plus. Ability to translate complex technical topics into business solutions and strategies, and to lead in a lean, agile environment using Scaled Agile principles. Strong planning, organization, execution, and time management skills; ability to lead and mentor junior engineers. 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. Compensation
The listed annualized base pay range is based on external market analysis. Actual base pay may vary based on factors including performance and demonstrated competencies. The base pay is one component of The Hartfords total compensation package, which may also include bonuses, incentives, and other rewards. The annualized base pay range for this role is:
$135,040 - $202,560 . Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age About Us | Our Culture | What Its Like to Work Here | Perks & Benefits #J-18808-Ljbffr
Sr Staff AI Data Engineer
role at
The Hartford . Sr AI Data Engineer is responsible for implementing AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready. Location & Schedule
Hybrid work schedule with in-office expectation 3 days per week (Tuesday through Thursday). Offices may include Columbus, OH; Chicago, IL; Hartford, CT; or Charlotte, NC. Responsibilities
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 Apache Kafka, AWS Kinesis, 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 reusable patterns. Develop graph database solutions for complex data relationships supporting AI systems. 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. Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. 8+ years of data engineering experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Bigdata, Cloud Technologies (AWS/Google/AZURE), Python/Spark, Datamesh, Datalake or Data Fabric. 3+ years of AI/ML experience, with 1+ years of data engineering experience focused on supporting Generative AI technologies. Strong hands-on experience implementing production ready enterprise grade AI data solutions. Experience with prompt engineering techniques for large language models. Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models. Experience of vector databases and graph databases, including implementation and optimization. Experience in processing and leveraging unstructured data for AI applications. Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Langchain, Langgraph). Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow. Experience with building AI pipelines that bring together structured, semi-structured and unstructured data including extraction, chunking, embedding and grounding strategies, semantic modeling, and preparing data for models and agentic solutions. Experience in vector databases, graph databases, NoSQL, Document DBs (e.g., AWS OpenSearch, Neo4j, MongoDB, DynamoDB). Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform. Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). Strong written and verbal communication skills and ability to explain technical concepts to various stakeholders. Experience in multi-cloud hybrid AI solutions. AI Certifications; experience in P&C or Employee Benefits industry. Knowledge of natural language processing (NLP) and computer vision technologies; contributions to open-source AI projects or research in Generative AI are a plus. Ability to translate complex technical topics into business solutions and strategies, and to lead in a lean, agile environment using Scaled Agile principles. Strong planning, organization, execution, and time management skills; ability to lead and mentor junior engineers. 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. Compensation
The listed annualized base pay range is based on external market analysis. Actual base pay may vary based on factors including performance and demonstrated competencies. The base pay is one component of The Hartfords total compensation package, which may also include bonuses, incentives, and other rewards. The annualized base pay range for this role is:
$135,040 - $202,560 . Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age About Us | Our Culture | What Its Like to Work Here | Perks & Benefits #J-18808-Ljbffr