Senior Engineer – GenAI Platform Automation

Bank of America

Senior platform automation engineer at Bank of America focusing on Generative AI and advanced analytics capabilities. Driving automation initiatives to enhance developer productivity and operational efficiency across the organization.

Posted 7/21/2026full-timePennington • New Jersey • 🇺🇸 United StatesSenior💰 $122,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Automation Engineering, CI/CD Pipeline Design, and Infrastructure-as-Code using Terraform, while leading enterprise-level AI and Data Science platform initiatives. Proven ability to collaborate with cross-functional teams to ensure compliance and operational excellence in complex distributed systems.

Highest-signal resume keywords

Automation FrameworksCI/CD Pipeline DesignInfrastructure-as-CodeCloud EngineeringPython Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Automation EngineeringCI/CD PipelinesInfrastructure-as-CodeTerraformKubernetesEvent-Driven ArchitecturesData ScienceGenerative AIDistributed ComputingObservability Frameworks

Soft Skills

Effective CommunicationTechnical LeadershipMentorship

Tools & Technologies

Atlassian ToolsBitbucketBambooJiraConfluenceKafkaJupyterVSCode

Industry Keywords

Platform EngineeringCloud EngineeringAI/MLData EngineeringGovernance Frameworks

Tech Stack

Tools & technologies

CloudDistributed SystemsKafkaKubernetesPythonTerraformYarn

About the role

Key responsibilities & impact

Ensure that the design and engineering approach for complex features are consistent with the larger portfolio solution
Define the technology tool stack for the solution and evaluate and adapt new testing tool/framework/practices for team(s)
Enable team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engage with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline
Guide and influence team(s) on design and best practices for high code performance
Provide end-to-end delivery of complex features, including automation, for either a single team or multiple teams, at the program level
Conduct research, design prototyping and other exploration activities such as evaluating new toolsets and components for release management, CI/CD, and features
Work with stakeholders to establish high-level solution needs and with architects for technical requirements
Lead automation initiatives for enterprise GenAI, Data Science, Metadata, Data Quality, Event Streaming, and Analytics platforms
Design and implement self-service automation capabilities that streamline onboarding, environment provisioning, deployment, governance, monitoring, and operational workflows
Build automated platform services supporting the complete AI and analytics lifecycle including data preparation, experimentation, model training, deployment, inferencing, observability, and lifecycle management
Develop Infrastructure-as-Code (IaC) solutions using Terraform and related automation frameworks to enable repeatable, scalable, and compliant infrastructure deployments
Design and implement enterprise CI/CD pipelines, automated testing frameworks, deployment automation, and release management processes using Atlassian and related DevOps toolchains
Partner with platform engineering and cloud teams to automate Kubernetes, container, serverless, and distributed computing environments
Build automation solutions supporting agentic AI applications, MCP-enabled services, event-driven architectures, and enterprise AI workflows
Drive operational excellence through platform monitoring, observability, automated remediation, performance optimization, and reliability engineering practices
Collaborate with architecture, engineering, governance, security, and business stakeholders to ensure platforms meet enterprise standards and compliance requirements
Conduct technical design reviews, automation assessments, code reviews, and establish engineering best practices across teams
Provide technical leadership, mentorship, and guidance to engineering teams adopting automation-first development and operational practices
Support key business initiatives including Consumer AML Analytics and other strategic AI platform adoption efforts

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or job related field required
10+ years of hands-on experience in platform engineering, automation engineering, cloud engineering, DevOps, or large-scale distributed systems
Proven experience building self-service enterprise platforms supporting AI/ML, Data Science, Data Engineering, and advanced analytics workloads
Strong expertise in automation frameworks, DevOps methodologies, CI/CD pipelines, Infrastructure-as-Code, and software delivery lifecycle automation
Deep understanding of modern open-source Generative AI and Data Science platform architectures including storage and compute separation, interactive development environments, virtual environments, containers, Jupyter, VSCode, and developer productivity tooling
Hands-on experience implementing enterprise CI/CD automation using Atlassian ecosystem tools including Bitbucket, Bamboo, Jira, and Confluence
Experience designing and implementing Infrastructure-as-Code solutions using Terraform and cloud-native automation frameworks
Strong understanding of metadata management, data lineage, governance frameworks, and semantic layer concepts supporting enterprise AI and data platforms
Experience building scalable cloud-native solutions utilizing distributed computing architectures and modern platform engineering principles
Experience automating deployments and operations for Kubernetes, containerized, YARN, serverless, and distributed processing environments
Experience designing and supporting event-driven architectures leveraging technologies such as Kafka and streaming data platforms
Working knowledge of agentic AI architectures, MCP frameworks, API integrations, workflow automation, and enterprise AI enablement platforms
Strong Python development experience for automation, orchestration, scripting, tooling, and operational engineering use cases
Knowledge of cloud engineering principles including networking, infrastructure management, security, resilience, scalability, and cost optimization
Experience implementing observability frameworks including logging, monitoring, tracing, alerting, automation, and operational dashboards
Ability to communicate effectively with engineers, architects, product owners, and business stakeholders across varying

Benefits

Comp & perks

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