Senior Data AI Engineer

01460 Continental Casualty Company; Chicago (IL); Hybrid; USD 72,000 - 141,000; Full time

Benefits offered by this job

Hybrid work model

Benefits package

Career development

Job summary

CNA in Chicago, IL is seeking a senior data engineer to design and build AI/data analytics platforms that migrate and modernize data from legacy systems to the cloud. You will architect scalable data pipelines, apply OCR/NLP, and implement vector databases for RAG-enabled AI workloads.

Ideal candidates have 7+ years in data engineering or AI/ML, strong Python/SQL/Java skills, and hands-on experience with GCP, BigQuery, Vertex AI, and distributed processing.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or related field; Master’s preferred.
• Typically 7+ years of experience in data engineering, AI or ML.
• 2+ years of coding proficiency in Python, Java, or SQL.

Responsibilities

• Design and build AI/data analytics platforms and migration pipelines.
• Develop scalable ingestion/transformation pipelines for structured and unstructured data.
• Implement vector databases and embedding pipelines for RAG and semantic search.
• Operate ML pipelines in DevOps/MLOps with testing, monitoring, and rollback.

Skills

Data engineering

AI/ML

Python

SQL

Java

GCP

BigQuery

Spark

NLP

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Vertex AI

Pinecone

pgvector

Dataflow

BigQuery

Cloud Run

Pub/Sub

Apache Spark

Job description

Essential Duties & 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.
• Productionize and operationalize AI solutions and advanced analytics in a DevOps/MLOps environment, including automated testing, monitoring, and rollback capabilities.
• Cultivate innovation by proactively proposing new ideas and identifying the right combination of tools and frameworks to turn business problems into analytics solutions.
• Researches, identifies and implements process improvements that address complex technology gaps.
• Builds strong knowledge of technology enablers.
• 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

• Bachelor's Degree in Computer Science, Engineering, Mathematics, Computational Statistics, Data Science, or a related technical field (or equivalent experience); Master's Degree preferred.
• Typically 7+ years of experience in data engineering, Artificial Intelligence or Machine Learning.
• 2+ years of coding proficiency in at least one programming language (Python, Java, SQL).
• Applicable certifications preferred (GCP, Data Engineering).

#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 [e-mail].

At CNA, we are focused on success, individually and collectively. We pride ourselves on promoting a culture that challenges and engages people. We strive to connect people, departments and business areas, to function as a team, and to serve our customers and communities with professionalism and respect. Our dedication to employee engagement, continuous learning and the open exchange of ideas is the cornerstone of our business.

These ideals, combined with our focus on the customer, enable us to explore new market opportunities and build on our success.

Our values, culture and financial strength are what differentiates us from other employers and make CNA the place you want to work.

At CNA, we are committed to advancing a culture of inclusion – one that attracts talent from all walks of life, foster respect and collaboration, and enables all of our colleagues to do their best work.

At CNA, we have a long standing commitment to the diverse communities in which we live and work. We actively make a difference for the greater good through partnerships, sustainability, initiatives, and working together for a better tomorrow.

Corporate Social Responsibility is not one person, or one department, it's the entire enterprise coming together to make the world a better place.