Principal Gen AI Data Architect

Dir Data Architecture - GT06AE

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 highly skilled and innovative Principal GenAI Architect to join our cutting-edge team. The ideal candidate will have deep, hands on expertise in generative AI technologies, a strong background in designing and implementing AI pipelines, and extensive knowledge of vector and graph databases. We're looking for someone with proven experience in prompt engineering, unstructured data processing, and agentic workflow design.

As the Principal GenAI Architect, you will lead the architecture and development of advanced AI systems that leverage state-of-the-art generative models, design efficient RAG (Retrieval-Augmented Generation) architectures, complex autonomous agentic frameworks and integrate seamlessly with our data infrastructure. The ideal candidate will also have familiarity with Snowflake integration and insurance industry-specific use cases, bringing a unique blend of technical expertise and domain knowledge to our team.

This role can have a Hybrid or Remote work arrangement.  Candidates who live near one of our office locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday)  Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise.

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.

Key Responsibilities:

• Hands on experience designing and developing end-to-end generative AI pipelines, from data ingestion to pipeline deployment and monitoring.
• Lead the architecture and implementation of complex agentic frameworks, ensuring best practices in software engineering and data integrations.
• Collaborate with cross-functional teams (Technology, Business, Platform etc.) to integrate GenAI solutions into existing data products and services.
• Stay at the forefront of GenAI advancements and incorporate new technologies and methodologies into our systems.
• Mentor and guide junior AI data engineers and architects in best practices for GenAI development.
• Design and implement optimized RAG architectures and pipelines.
• Design and implement strategies for handling unstructured data in AI pipelines.
• Design and implement agentic workflows for autonomous AI systems.
• Design and implement 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.
• Build POCs to compare evaluate various emerging technologies around data and AI
• Create prototypes to establish patterns.

Required Qualifications:

• Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
• 15+ years of experience in data engineering, with at least 3 years focused on generative AI technologies.
• Expertise in designing and architecting production-ready enterprise grade GenAI pipelines.
• Expertise in prompt engineering techniques for large language models.
• Expertise in architecting and implementing sophisticated Retrieval-Augmented Generation (RAG) pipelines, integrating advanced retrieval mechanisms with state-of-the-art language models.
• Strong knowledge of 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.)
• Expertise in designing, loading, and querying graph databases for GenAI applications.
• Extensive experience in processing and leveraging unstructured data for GenAI applications.
• Proficiency in designing and implementing scalable agentic workflows for AI systems. (AWS (Lambda, S3, EC2, SageMaker) , Langchain, Langgraph etc. or GCP Vertex AI , embedding, chunking and grounding strategies)
• Strong programming skills in Python and knowledge of deep learning frameworks such as PyTorch or TensorFlow.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
• Excellent communication skills and ability to explain complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

• Experience designing mult