Data Engineer – Python, AI

Bank of America

Data Engineer developing and delivering AI-driven data solutions at Bank of America. Collaborating with product and engineering teams to enhance enterprise lending processes and performance.

Posted 6/4/2026full-timeCharlotte • North Carolina • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

DockerJenkinsMicroservicesOpenShiftPythonSDLC

About the role

Key responsibilities & impact

developing and delivering data solutions to accomplish technology and business goals and initiatives
performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems
working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains
designing and productionizing AI-driven capabilities that deliver measurable efficiency gains, improved operational resilience, and smarter decisioning across large-scale enterprise lending platforms
working closely with product, operations, and engineering teams to build, deploy, and scale ML and GenAI solutions embedded into mission-critical platforms, while adhering to enterprise standards for security, compliance, and model governance
designing, building, and operating AI/ML solutions end-to-end, with strong emphasis on MLOps, ML lifecycle management, and production readiness

Requirements

What you’ll need

Bachelor's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related
6+ years overall experience in software engineering with strong hands-on development in Python
3+ years of hands-on AI/ML experience, building and deploying machine learning models and Gen AI solutions using locally hosted LLMs in production environments
Proven experience productionizing ML models using MLflow and enterprise-grade MLOps frameworks
Strong understanding of the end-to-end ML lifecycle: data preparation, feature engineering, training, validation, deployment, monitoring, and retraining
Experience building RESTful APIs and microservices to expose ML capabilities
Hands-on experience with CI/CD pipelines, automation, and DevOps practices for ML and application workloads
Experience with containerization and deployment technologies (e.g., Openshift, Docker or equivalent enterprise platforms)
Proficiency with version control and enterprise SDLC tools (Git/Bitbucket, Jenkins, pytest, SonarQube, Artifactory, etc.)
Experience working in large, multi-team enterprise environments with shared codebases and governance standards
Strong analytical, problem-solving, and communication skills with ability to engage business and technical stakeholders.

Benefits

Comp & perks

affordable, competitive and flexible benefits
health insurance
retirement plans
paid time off
professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonAI/MLMLOpsML lifecycle managementdata preparationfeature engineeringtrainingvalidationdeploymentmonitoring

Soft Skills

analytical skillsproblem-solvingcommunication skillsstakeholder engagement

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Computer Information SystemsBachelor's degree in Management Information SystemsBachelor's degree in Engineering