Senior Engineer-GenAI Platform Engineering

Job Description:

At Bank of America we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients teammates communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed build a career and contribute to our shared success. This includes attracting and developing exceptional talent recognizing and rewarding performance and supporting our teammates physical emotional and financial wellness through affordable competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service community college education or a wide range of work and life experiences. These journeys foster resilience leadership and innovation strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration engagement and career development. Our approach includes clear in-office expectations while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America you can build a successful career with opportunities to learn grow and make an impact. Join us!

Position Summary:

This is a senior platform engineering role responsible for architecting building and advancing Bank of Americas 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. The ideal candidate combines deep technical expertise with strong leadership skills a passion for innovation and the ability to translate complex business needs into enterprise-grade platform capabilities.

This job is responsible for defining and leading the engineering approach for complex features to deliver significant business outcomes. 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.

Responsibilities:

• Ensures 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)
• Enables team(s)/applications with Continuous Integration/Continuous Development (CI/CD) capabilities and engages with other technical stakeholders pertaining to efficient functioning of CI-CD pipeline
• Guides and influences team(s) on design and best practices for high code performance e.g. pairing code reviews
• Provides end-to-end delivery of complex features including automation for either a single team or multiple teams at the program level
• Conducts research design prototyping and other exploration activities such as evaluating new toolsets and components for release management CI/CD and features
• Works with stakeholders to establish high-level solution needs and with architects for technical requirements
• Provide technical leadership architectural direction and platform engineering expertise across enterprise Generative AI Data Science Data Engineering Event Streaming Metadata and Data Quality initiatives.
• Design and develop reusable platform services that enable end-to-end self-service AI and data workflows including data onboarding data preparation experimentation model development evaluation deployment monitoring governance and observability.
• Define and implement enterprise standards reference architectures and engineering best practices for scalable AI and data platforms.
• Lead the design and delivery of agentic AI applications intelligent workflows MCP-enabled services and event-driven architectures using modern open-source technologies.
• Partner with business product architecture and engineering teams to gather requirements evaluate technologies prototype solutions and accelerate innovation.
• Drive platform modernization initiatives leveraging cloud-native architectures Kubernetes containers serverless services distributed computing and modern data processing frameworks.
• Ensure platform solutions meet enterprise requirements for security governance resiliency scalability availability compliance and operational excellence.
• Establish and enforce CI/CD Infrastructure-as-Code automation and DevSecOps practices to improve developer productivity and platform reliability.
• Provide technical mentorship conduct architecture reviews perform code reviews and champion engineering excellence across teams.
• Own critical technology decisions and communicate architectural direction effectively to technical and executive stakeholders.

Required Qualifications

• Bachelors or Masters 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.

Preferred Qualifications

• Experience building enterprise-wide GenAI ecosystems including AI gateways model management prompt management vector databases agent orchestration and responsible AI capabilities.
• Experience with Retrieval-Augmented Generation (RAG) agentic architectures MCP servers AI workflow orchestration and enterprise knowledge platforms.
• Strong knowledge of cloud-native AI and data platforms across public and private cloud environments.
• Experience with developer platforms internal AI copilots self-service data products and platform product management.
• Experience establishing enterprise AI governance compliance risk controls and responsible AI practices.
• Demonstrated success leading large-scale platform transformations and modernizing legacy analytics and data science ecosystems.

Skills:

• Automation
• Influence
• Result Orientation
• Stakeholder Management
• Technical Strategy Development
• Application Development
• Architecture
• Business Acumen
• Risk Management
• Solution Design
• Agile Practices
• Analytical Thinking
• Collaboration
• Data Management
• Solution Delivery Process

Shift:

1st shift (United States of America)

Hours Per Week:

40

Pay Transparency details

US - NJ - Pennington - 1500 American Blvd - Hopewell Bldg 5 (NJ2150)

Pay and benefits information

Pay range

$122000.00 - $200000.00 annualized salary offers to be determined based on experience education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors the performance and contributions of their line of business and/or group; and the overall success of the Company.

Benefits

This role is currently benefits eligible. 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.