Sr. Staff AI Data Engineer

The Hartford-posted 4 months ago
$135,040 - $202,560/Yr
Full-time • Senior
Hybrid • Hartford, CT
Insurance Carriers and Related Activities
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We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future. 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. This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

  • 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 adoption of reusable patterns.
  • Develop graph database solution 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.
  • 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.
  • Experience in vector databases, graph databases, NoSQL, Document DBs, including design, implementation, and optimization.
  • 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 publications in the field of Generative AI.
  • Strong technical knowledge (AI solution leveraging Cloud and modern solutions).
  • Able to communicate effectively with both technical and non-technical teams and influence.
  • Collaboration across teams, decision making, conflict resolution and relationship building skills.
  • Experience in mentoring and developing Junior AI or Data Engineers.
  • Knowledge of evolving industry design patterns for AI.
  • Strong planning, organization, and execution skills.
  • Ability to provide Thought Leadership to dynamic and collaborative teams, demonstrating excellent interpersonal skills and time management capabilities.
  • Ability to understand and align deliverables to the departmental and organization strategies and objectives.
  • Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working.
  • Leader and team player with a transformation mindset.
  • Ability to translate complex technical topics into business solutions and strategies, as well as turn business requirements into a technical solution.
  • Experience in P&C or Employee Benefits industry.
  • AI Certifications.
  • Contributions to open-source AI projects or research publications in the field of Generative AI.
  • The base pay is just one component of The Hartford's total compensation package for employees.
  • Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition.
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