Senior GenAI Platform Architect & Engineer

Bank of America; Pennington (NJ); On-site; USD 122,000 - 200,000; Full time

Benefits offered by this job

Benefits eligible

Annual discretionary plan

Job summary

Bank of America is seeking a senior platform engineer to architect and advance enterprise‑scale Generative AI and data platforms. You will lead scalable, secure, and self‑service AI solutions across multiple lines of business, partnering with architects, product owners, and data scientists.

You will shape strategy, define standards, and deliver reusable platform services with modern data architectures, event streaming, and Kubernetes‑driven deployments.

Qualifications

• 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.

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 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.

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

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related technical discipline

Job description

Bank of America is seeking a senior platform engineer to architect and advance enterprise‑scale Generative AI and data platforms. You will lead scalable, secure, and self‑service AI solutions across multiple lines of business, partnering with architects, product owners, and data scientists.

You will shape strategy, define standards, and deliver reusable platform services with modern data architectures, event streaming, and Kubernetes‑driven deployments.