You have a clear vision of where your career can go. And we have the leadership to help you get there. 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.

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. The engineer works across structured and unstructured data domains — including documents, images, audio, and transactional records — to unlock analytical value through scalable pipelines, RAG architectures, vector databases, and knowledge graphs. This role may also provide guidance to others to support the building of complex technical capabilities.

JOB DESCRIPTION:

Essential Duties & Responsibilities

Performs a combination of duties in accordance with departmental guidelines:

May perform additional duties as assigned.

Reporting Relationship

Typically Director or above

Skills, Knowledge & Abilities

• 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.

• Proven experience designing and implementing vector databases (e.g., Vertex AI Vector Search, Pinecone, pgvector), embedding pipelines, and knowledge graph structures that underpin RAG and semantic search applications

• Strong SQL and data analytical skills; experience building data marts and feature datasets for data science and ML applications.

• Strong coding fluency in Python; hands-on experience with BigQuery, Claude Code, RAG architectures, LLMs, ADK, and prompt engineering techniques

• Expertise in building ML platforms and data pipelines at scale; familiarity with major ML algorithms, deep learning, NLP, information retrieval, and data mining 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.

• Solid experience managing diverse data sources including preprocessing, cleansing, and verifying data integrity to meet data science and ML requirements

• Demonstrated experience with machine learning, deep learning, information retrieval, NLP, or data mining — particularly applied to unstructured or semi-structured data

• Hands-on experience with vector databases, embedding models (e.g., text-embedding-gecko, OpenAI Ada, Cohere), and end-to-end RAG pipeline design

• Experience using Agile methods preferred.

• Strong communication and interpersonal skills and the ability to work effectively with peers and team members in a highly matrixed environment.

• Preferred experience with the insurance industry, its products and services.

• Experience in implementing big data processing technology. Apache Spark preferred.

Education & Experience

#LI-KJ1 #LI-HYBRID

In certain jurisdictions, CNA is legally required to include a reasonable estimate of the compensation for this role. 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. Salary determinations are based on various factors, including but not limited to, relevant work experience, skills, certifications and location. CNA offers a comprehensive and competitive benefits package to help our employees – and their family members – achieve their physical, financial, emotional and social wellbeing goals. For a detailed look at CNA’s benefits, please visit cnabenefits.com.

CNA utilizes AI-enabled technology during the recruiting process. For more information, please visit our careers page.

CNA is committed to providing reasonable accommodations to qualified individuals with disabilities in the recruitment process. To request an accommodation, please contact leaveadministration@cna.com