AI Data Engineer - Hybrid

Staff AI Data Engineer - Hybrid

We are committed to making a difference and are proud to be an insurance company that goes beyond coverages and policies. Working here provides opportunities to achieve your goals and help others do the same. Join us as we shape the future of technology in AI and data engineering!

Primary Job Responsibilities

• Implement AI data pipelines integrating structured, semi-structured, and unstructured data to support AI and Agentic solutions, including pre-processing, extraction, chunking, embedding, and grounding strategies.
• Develop AI-driven systems to enhance data capabilities while ensuring industry compliance.
• Implement Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.
• Collaborate with cross-functional teams to embed solutions into operational processes and systems.
• Stay updated on industry advancements in GenAI and apply modern technologies accordingly.
• Design, build, and maintain scalable real-time data streaming pipelines using technologies like Apache Kafka, AWS Kinesis, or Spark streaming.
• Create data domains and products for reporting, data science, AI/ML, and analytics.
• Ensure reliability, scalability, and availability of data pipelines through monitoring and incident management.
• Implement best practices in reliability engineering, including redundancy and disaster recovery.

Skills

• Strong technical knowledge of AI solutions leveraging cloud and modern solutions.
• Effective collaboration, decision-making, conflict resolution, and relationship-building skills.
• Knowledge of industry design patterns for AI.
• Planning, organization, and execution skills at an intermediate level.
• Thought leadership and excellent interpersonal and time management skills.
• Ability to align deliverables with organizational strategies.
• Experience in agile environments, leveraging Scaled Agile principles.
• Ability to translate complex technical topics into business solutions.

Qualifications

• Bachelor's degree in Computer Science, AI, or related field.
• 5+ years in data engineering, including SQL, No
  
  SQL, Snowflake, ETL/ELT, cloud technologies (AWS, Google Cloud, Azure), Python/Spark, Data Mesh, Data Lake, or Data Fabric.
• 1+ year supporting Generative AI technologies.
• Experience with enterprise-grade GenAI data solutions and prompt engineering for large language models.
• Experience with RAG pipelines, vector and graph databases, and unstructured data processing.
• Proficiency in Python and deep learning frameworks such as PyTorch or Tensor Flow.
• Experience with cloud platforms and containerization technologies.
• Excellent communication skills to explain technical concepts to stakeholders.

Preferred Qualifications

• Experience with multi-cloud hybrid AI solutions.
• AI certifications.
• Knowledge of NLP and computer vision.
• Contributions to open-source AI projects or research publications in Generative AI.

Compensation

The annual base pay ranges from $125,760 to $188,640, based on market analysis and individual factors. Compensation may include bonuses and incentives.

We are an equal opportunity employer committed to diversity and inclusion.