AI Data Engineer - Hybrid

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.   

We are seeking a talented and motivated AI Data Engineer to join our innovative team. The ideal candidate will have strong expertise in generative AI technologies, experience in implementing AI pipelines, and knowledge of vector and graph databases. We're looking for someone with hands-on experience in prompt engineering, unstructured data processing, and agentic workflow implementation. As a Senior AI Data Engineer, you will contribute to the development of advanced AI systems that leverage state-of-the-art generative models, implement efficient RAG (Retrieval-Augmented Generation) architectures, and integrate with our data infrastructure. Familiarity with Snowflake integration and insurance industry use cases is a plus.

This role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).

Primary Job Responsibilities

• Design, develop, and implement complex data pipelines for AI/ML, including those supporting RAG architectures, using technologies such as Python, Snowflake, AWS, GCP, and Vertex AI.
• Implement end-to-end generative AI pipelines, from data ingestion to pipeline deployment and monitoring.
• Build and maintain data pipelines that ingest, transform, and load data from various sources (structured, unstructured, and semi-structured) into data warehouses, data lakes, vector databases (e.g., Pinecone, Weaviate, Faiss - consider specifying which ones you use or are exploring), and graph databases (e.g., Neo4j, Amazon Neptune - same consideration as above).
• Develop and implement data quality checks, validation processes, and monitoring solutions to ensure data accuracy, consistency, and reliability.
• Implement end-to-end generative AI data pipelines, from data ingestion to pipeline deployment and monitoring.
• Develop complex AI systems, adhering to best practices in software engineering and AI development.
• Work with cross-functional teams to integrate AI solutions into existing products and services.
• Keep up-to-date with AI advancements and apply new technologies and methodologies to our systems.
• Implement and optimize RAG architectures and pipelines.
• Develop solutions for handling unstructured data in AI pipelines.
• Implement agentic workflows for autonomous AI systems.
• Develop graph database solutions for complex data relationships in AI systems.
• Integrate AI pipelines with Snowflake data warehouse for efficient data processing and storage.
• Apply GenAI solutions to insurance-specific use cases and challenges.

Required Qualifications:

• Candidates 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.
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
• 3+ years of experience in data engineering, with at least 2 years focused on generative AI technologies.
• Strong experience in implementing production-ready enterprise-grade GenAI pipelines.
• Experience with prompt engineering techniques for large language models.
• Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.
• Knowledge of vector databases and graph databases, including implementation and optimization.
• Experience in processing and leveraging unstructured data for GenAI applications.
• Proficiency in implementing agentic workflows for AI systems.
• Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Proficiency in implementing scalable agentic workflows for AI systems. (AWS (Lambda, S3, EC2, SageMaker) , Langchain, Langgraph etc. or GCP Vertex AI , embedding, chunking and grounding strategies)
• Experience in vector databases, graph databases, NoSQL, Document DBs , including design, implementation, and optimization. (e.g. AWS open search or GCP Vertex AI, neo4j etc. Mongo, Dynamo etc.)
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
• Good communication skills and ability to explain technical concepts to various stakeholders.

Preferred Qualifications:

• Experience in multi cloud hybrid AI solutions.
• Experience with Open search, Vector stores/search, Vertex AI and Graph db.
• Experience in building/designing autonomous AI agents
• 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.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. 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. The annualized base pay range for this role is:

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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