CNA
Senior Data AI Engineer
Chicago, IL, USA · Senior
Sponsorship not specified$72k-$141kDetected 13 days ago
PythonJavaAlgorithmsSQLBigQueryVector DatabasesGCPCloud PlatformsDevOpsMachine LearningDeep LearningSparkData EngineeringData ScienceNLPLLMsRAGMLOpsStatisticsTest AutomationLeadershipCommunication
About the role
- You have a clear vision of where your career can go.
- And we have the leadership to help you get there.
- In District of Columbia, California, Colorado, Connecticut, Illinois, Maryland, Massachusetts, New York and Washington, the national base pay range for this job level is $72,000 to $141,000 annually.
Responsibilities
- Design and build AI solutions that accelerate data migration from legacy systems to the cloud, ensuring scalability, reliability, and governance compliance.
- Design and implement scalable ingestion and transformation pipelines across structured (SQL, relational) and unstructured (documents, images, audio, email, call transcripts) data sources, applying OCR, NLP preprocessing, and document chunking strategies optimized for LLM consumption.
- Implement modern lakehouse patterns on Google Cloud Platform (GCP) - including data governance, cataloging, and lineage tracking - to ensure data is reliably discoverable, auditable, and fit for AI/ML workloads at scale.
- Design and implement vector databases, embedding pipelines, and knowledge graph structures that serve as the foundational retrieval layer for RAG and other AI applications.
- Researches, identifies and implements process improvements that address complex technology gaps. Builds strong knowledge of technology enablers.
- Deep expertise building scalable ingestion and transformation pipelines across structured and unstructured data sources; strong background migrating workloads from legacy systems to modern cloud platforms.
- Skilled in parsing and normalizing diverse content types - PDFs, emails, images, and call transcripts - using OCR, NLP preprocessing (tokenization, entity extraction, summarization), and document chunking strategies optimized for LLM consumption.
- Strong SQL and data analytical skills; experience building data marts and feature datasets for data science and ML applications.
- At CNA, we strive to create a culture in which people know they matter and are part of something important, ensuring the abilities of all employees are used to their fullest potential.
- This role may also provide guidance to others to support the building of complex technical capabilities.
Requirements
- Strong coding fluency in Python; hands-on experience with BigQuery, Claude Code, RAG architectures, LLMs, ADK, and prompt engineering techniques
- Experience with GCP services (Vertex AI, Dataflow, BigQuery, Cloud Run, Pub/Sub); comfort with distributed computing frameworks (Apache Spark, Dataproc) for large-scale data processing.
Compensation
- I n certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role.
Benefits
- A senior individual contributor role responsible for designing, building, and operationalizing end-to-end AI and machine learning solutions that accelerate CNA's migration to a modern cloud data lakehouse.
- Expertise in building ML platforms and data pipelines at scale; familiarity with major ML algorithms, deep learning, NLP, information retrieval, and data mining techniques
This listing is sourced directly from CNA's careers page and normalized into a canonical job model.