Senior Engineer – GenAI Platform Engineering

Bank of America

Senior Engineer responsible for architecting and building Generative AI solutions at Bank of America. Leading design and delivery of enterprise platform services across multiple business lines.

Posted 7/30/2026full-timePennington • New Jersey • 🇺🇸 United StatesSenior💰 $122,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in architecting and building enterprise-scale Generative AI and data platforms, with a strong focus on modern AI/ML ecosystems, cloud-native architectures, and CI/CD practices. Proven ability to lead cross-functional teams and drive platform modernization initiatives while ensuring engineering excellence.

Highest-signal resume keywords

Generative AI Platform ArchitectureCloud-Native ArchitectureCI/CD ImplementationPython ProgrammingData Engineering

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Applicant Tracking System Keywords

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Hard Skills

Enterprise-Scale AI DesignData ScienceData QualityEvent-Driven ArchitectureStreaming ArchitectureMetadata-Driven PlatformsAPI DevelopmentMicroservicesDistributed SystemsInfrastructure Automation

Soft Skills

Technical MentorshipCollaborationEngineering Excellence

Tools & Technologies

KubernetesContainersCloud-Native EnvironmentsDevSecOps PracticesAutomated Testing

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s Degree in Engineering

Industry Keywords

AI/ML LifecyclePlatform ObservabilityMonitoringSecurityGovernanceReliability

Tech Stack

Tools & technologies

CloudDistributed SystemsKubernetesMicroservicesPython

About the role

Key responsibilities & impact

Architecting, building, and advancing Bank of America’s enterprise-scale Generative AI
Define the strategy, architecture, and engineering standards for AI and data platforms
Lead the design and delivery of reusable enterprise platform services
Work closely with architects, product owners, engineers, and business stakeholders
Build highly scalable, secure, and resilient platforms
Drive platform modernization initiatives leveraging cloud-native architectures and modern data processing frameworks
Establish and enforce CI/CD, Infrastructure-as-Code, and DevSecOps practices
Provide technical mentorship and champion engineering excellence across teams

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical discipline
10+ years of hands-on experience designing and building enterprise-scale AI, Data Science, Data Engineering, Metadata, Data Quality, and Analytics platforms
Proven experience architecting and implementing enterprise Generative AI platforms
Strong experience building self-service platforms supporting the complete AI/ML lifecycle
Deep understanding of modern AI and data platform architectures
Experience designing and implementing metadata-driven platforms
Hands-on expertise with Python and modern AI/ML ecosystems
Strong experience designing event-driven and streaming architectures
Experience building and deploying scalable AI and data workloads on Kubernetes, containers, virtualized infrastructure, and cloud-native environments
Practical experience developing enterprise-grade APIs, microservices, and distributed systems
Experience implementing CI/CD, automated testing, infrastructure automation, and DevSecOps practices
Strong understanding of platform observability, monitoring, security, governance, and reliability
Proven ability to collaborate with cross-functional teams

Benefits

Comp & perks

Industry-leading benefits
Access to paid time off
Resources and support to make a genuine impact
Contribute to the sustainable growth of our business and the communities we serve