Sr Staff AI Data Engineer - Hybrid

Sr Staff Data Engineer - GE07DE

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.

Join our team as a Senior Staff AI Data Engineer and lead the charge in developing cutting-edge AI solutions and data engineering strategies. Embrace our core values of innovation, collaboration, and excellence as you unlock unparalleled growth opportunities in the dynamic field of AI and data engineering. Shape the future of technology with us! Apply now to be part of our innovative journey and make a significant impact!

• 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 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 GenAI 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 GenAI 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.

• 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.

• Bachelor's 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.
• 1+ years of data engineering experience focused on supporting Generative AI technologies
• Strong hands-on experience implementing production ready enterprise grade GenAI 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 GenAI 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. 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.).
• 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.