Senior AI Engineer — GenAI & Finance ML Architect

AbbVie; North Chicago (IL); On-site; USD 130,000 - 190,000; Full time

Job summary

AbbVie seeks a highly skilled AI/ML engineer to design and deploy ML/AI solutions for financial use cases. You’ll lead technical architecture for traditional and generative AI models, shaping data pipelines, deployment standards, and governance across the stack.

You will collaborate with risk, compliance, and business units, evaluating new AI technologies and ensuring auditability and reliability of AI systems. Strong AWS, MLOps, and Python expertise are essential.

Qualifications

• Bachelor’s degree with 6 years’ experience; Master’s with 5 years; PhD with 0 years.
• Strong theoretical and practical understanding of Python, data science, ML, generative AI and agentic AI approaches.
• Experience architecting solutions in an AWS environment.
• Experience developing robust data/model pipelines, APIs, and integration layers; implement MLOps for training, validation, deployment, monitoring.
• Proven ability to design secure, scalable AI architectures for finance use cases.

Responsibilities

• Conceive, design, engineer, and implement ML/AI solutions for financial use cases.
• Mentor junior engineers and lead projects to develop new products or improvements.
• Design secure, scalable architectures for AI/ML, generative AI, and agentic AI in finance.
• Configure AWS data pipelines, model hosting, vector search, orchestration, monitoring, and governance.
• Develop robust data/model pipelines, APIs, and integration layers; implement CI/CD and observability.

Skills

Python

Data science

Machine learning

Generative AI

Agentic AI

AWS

CI/CD

Security & compliance

Communication

Education

Bachelor’s degree

Master’s degree

PhD

Tools

AWS

GitHub

Vector search

MLOps tooling

Job description

AbbVie seeks a highly skilled AI/ML engineer to design and deploy ML/AI solutions for financial use cases. You’ll lead technical architecture for traditional and generative AI models, shaping data pipelines, deployment standards, and governance across the stack.

You will collaborate with risk, compliance, and business units, evaluating new AI technologies and ensuring auditability and reliability of AI systems. Strong AWS, MLOps, and Python expertise are essential.