AI-Driven Data Engineer: ML Lifecycle & MLOps Specialist

Quest Oracle Community; Charlotte, Northern (NC, KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Bank of America seeks an AI/ML focused data engineer to design and deliver data solutions for lending and payments platforms, embedding AI/ML capabilities while ensuring governance, security, and reliability. You will collaborate with product, operations, and engineering teams to deploy ML/GenAI solutions with robust MLOps practices, lifecycle management, and production readiness.

The role emphasizes cross‑functional collaboration, adherence to enterprise standards, and delivering measurable

Qualifications

• Bachelor's degree or equivalent in CS or related field.
• At least 6+ years in software engineering with Python.
• At least 3+ years in AI/ML deploying models in production.
• Experience productionizing ML models with MLflow and MLOps.
• Strong end-to-end ML lifecycle knowledge.
• Experience building RESTful APIs/microservices for ML.
• CI/CD, DevOps practices for ML and apps.
• Experience with containerization and enterprise platforms.

Responsibilities

• Collaborate with multiple teams to refine data requirements and deliverables.
• Develop data ingestion, transformation, and quality pipelines.
• Construct data pipelines for large datasets supporting data-driven decisions.
• Design and execute test plans; analyze results and triage issues.
• Lead IT projects to meet delivery timelines and standards.
• Document data engineering requirements for deployment and support.
• Partner with stakeholders to address data governance and standards.

Skills

Python

AI/ML

GenAI

RESTful APIs

CI/CD

DevOps

Data Transformation

Communication

Education

Bachelor's degree or equivalent in Computer Science or related

Tools

MLflow

OpenShift

Docker

Kubernetes

Git/Jenkins

Job description

Bank of America seeks an AI/ML focused data engineer to design and deliver data solutions for lending and payments platforms, embedding AI/ML capabilities while ensuring governance, security, and reliability. You will collaborate with product, operations, and engineering teams to deploy ML/GenAI solutions with robust MLOps practices, lifecycle management, and production readiness.

The role emphasizes cross‑functional collaboration, adherence to enterprise standards, and delivering measurable