Senior Engineer – GenAI Platform Automation

Bank of America

Senior Engineer focusing on platform automation for Generative AI and data analytics. Leading initiatives to improve developer productivity and operational efficiency at Bank of America.

Posted 7/20/2026full-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 platform automation, cloud-native technologies, and Infrastructure-as-Code, with a strong focus on delivering scalable and resilient automation solutions for AI and data platforms. Proficient in CI/CD methodologies and automation frameworks to enhance developer productivity and operational efficiency.

Highest-signal resume keywords

Platform Automation ExpertiseCloud-Native TechnologiesInfrastructure-as-Code (IaC)CI/CD Pipeline ImplementationPython Development for Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Platform EngineeringAutomation EngineeringDevOps MethodologiesGenerative AI Ecosystem ToolingDistributed ComputingTerraformKubernetesEvent-Driven ArchitecturesObservability FrameworksData Governance Frameworks

Soft Skills

Effective CommunicationTechnical Thought Leadership

Tools & Technologies

Atlassian Tools (Bitbucket, Bamboo, Jira, Confluence)JupyterVSCodeKafkaAgentic AI Architectures

Industry Keywords

AI/MLData ScienceData EngineeringAdvanced AnalyticsCloud Engineering Principles

Tech Stack

Tools & technologies

CloudDistributed SystemsKafkaKubernetesPythonTerraformYarn

About the role

Key responsibilities & impact

This is a senior platform automation engineering role focused on accelerating enterprise adoption of Generative AI, Data Science, Data Engineering, and Advanced Analytics capabilities across Bank of America.
The role will lead automation initiatives that improve developer productivity, platform reliability, operational efficiency, governance, and self-service adoption across enterprise AI and data platforms.
The successful candidate will be responsible for designing, building, and operationalizing automated platform capabilities spanning infrastructure provisioning, CI/CD, environment management, governance controls, observability, testing, deployment automation, and AI workload enablement.
The individual will work closely with platform engineering, cloud engineering, architecture, data science, and business teams to deliver scalable, secure, and resilient automation solutions supporting the full lifecycle of AI and analytics workloads.
This role requires strong expertise in platform automation, cloud-native technologies, Infrastructure-as-Code (IaC), DevSecOps, Generative AI ecosystem tooling, and distributed computing platforms.
The ideal candidate combines deep engineering expertise with a passion for automation, operational excellence, and continuous platform innovation.
Key responsibilities of the job include delivering complex features and technology, enabling development efficiencies, providing technical thought leadership based on conducting multiple software implementations, and applying both depth and breadth in a number of technical competencies.
Additionally, this job is accountable for end-to-end solution design and delivery.

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

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