Senior Engineer – GenAI Platform Engineering

Role Overview

• This is a senior platform engineering role responsible for architecting, building, and advancing Bank of America’s enterprise-scale Generative AI leveraging Data Science, Event Platform, Data Quality, Metadata, and Data Platform capabilities.
• The role will help define the strategy, architecture, and engineering standards for next-generation AI and data platforms that enable self-service, governed, and scalable solutions across Consumer, Banking, Wealth, and Enterprise organizations.
• The successful candidate will lead the design and delivery of reusable enterprise platform services that accelerate AI adoption, data-driven decision making, advanced analytics, agentic workflows, and digital transformation initiatives.
• This individual will work closely with architects, product owners, engineers, data scientists, and business stakeholders to build highly scalable, secure, and resilient platforms leveraging cloud-native technologies, distributed computing, modern data architectures, and Generative AI frameworks.
• This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes.

Requirements

• 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, including LLM integration, agent frameworks, retrieval systems, prompt orchestration, vector-enabled architectures, and AI governance capabilities.
• Strong experience building self-service platforms supporting the complete AI/ML lifecycle, including data ingestion, feature engineering, experimentation, model development, deployment, inferencing, monitoring, and observability.
• Deep understanding of modern AI and data platform architectures, including storage-compute separation, distributed processing, interactive development environments, containerization, and developer productivity tooling.
• Experience designing and implementing metadata-driven platforms, semantic layers, data lineage, data quality frameworks, knowledge graphs, and enterprise data governance solutions.
• Hands-on expertise with Python and modern AI/ML ecosystems, including open-source frameworks, libraries, and model-serving technologies.
• Strong experience designing event-driven and streaming architectures using technologies such as Kafka, Apache Spark, Flink, or equivalent distributed processing frameworks.
• 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 supporting high-volume data and AI workloads.
• Experience implementing CI/CD, automated testing, infrastructure automation, and DevSecOps practices using enterprise toolchains.
• Strong understanding of platform observability, monitoring, security, governance, reliability, recoverability, and operational excellence.
• Proven ability to collaborate with cross-functional teams, influence architectural decisions, and communicate complex technical concepts to diverse audiences.

Tech Stack

• Apache
• Cloud
• Distributed Systems
• Kafka
• Kubernetes
• Microservices
• Python
• Spark

Benefits

• Employees are eligible for an annual discretionary award based on individual performance results and behaviors, the performance and contributions of their line of business and/or group, and the overall success of the Company.
• We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.