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The Hartford · 1 month ago

Sr Staff Data Engineer - Hybrid

Hartford, CT

Full-time

Hybrid

Senior Level, Lead/Staff

$135K/yr - $203K/yr

8+ years exp

The Hartford is an insurance company that is focused on making a difference and helping others achieve their goals. The Sr Staff AI Data Engineer will be responsible for implementing AI data pipelines and developing AI-driven systems to improve data capabilities, while collaborating with cross-functional teams to integrate solutions into operational processes.

Auto InsuranceCommercial InsuranceEmployee BenefitsFinanceFinancial ServicesInsuranceLife InsuranceProperty Insurance

Responsibilities

AI Data Engineering lead 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

Develop AI-driven systems to improve data capabilities, ensuring compliance

With industry’s 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 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

Qualification

Data EngineeringAI Data PipelinesCloud TechnologiesPythonSQLNoSQLETL/ELT ToolsBig DataCICDDeep Learning FrameworksData GovernanceContainerizationCommunication SkillsMentoringCollaborationProblem Solving

Required

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field

8+ years of strong hands-on 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

Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow

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

Preferred

Experience in multi cloud hybrid AI solutions

AI Certifications

Experience in 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

Experience with building AI pipelines that bring together structured, semi-structured and unstructured data. This includes pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and getting the data ready for Models and Agentic solutions

Experience in vector databases, graph databases, NoSQL, Document DBs, including design, implementation, and optimization. (e.g., AWS open search, GCP Vertex AI, Neo4j, Spanner Graph, Neptune, Mongo, DynamoDB etc.)

3+ years of AI/ML experience, with 1+ years of data engineering experience focused on supporting Generative AI technologies

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)