Senior Engineer – GenAI Platform Automation

Job Description

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. Responsibilities include designing, building, and operationalizing automated platform capabilities spanning infrastructure provisioning, CI/CD, environment management, governance controls, observability, testing, deployment automation, and AI workload enablement.

• Ensure design and engineering approach for complex features are consistent with the larger portfolio solution.
• Define the technology tool stack for the solution and evaluate new testing tools and practices.
• Enable teams and applications with CI/CD capabilities and engage with technical stakeholders.
• Guide teams on design and best practices for high code performance, including pairing and code reviews.
• Provide end‑to‑end delivery of complex features, including automation, at the program level.
• Conduct research, design prototyping, and exploration activities such as evaluating new toolsets for release management, CI/CD, and features.
• Work with stakeholders to establish high‑level solution needs and collaborate with architects for technical requirements.
• Lead automation initiatives for enterprise Generative AI, 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, inference, observability, and lifecycle management.
• Develop Infrastructure‑as‑Code 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 Dev Ops tool chains.
• Partner with platform engineering and cloud teams to automate Kubernetes, containers, serverless, and distributed computing environments.
• Build automation solutions supporting agentic AI applications, MPC‑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, and 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.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or related field.
• 10+ years of hands‑on experience in platform engineering, automation engineering, cloud engineering, Dev Ops, 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, Dev Ops 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…