Senior Engineer - Enterprise GenAI Platform Architect

Bank of America•Jersey City, NJ

3d•$122,000 - $200,000•Onsite

About The Position

At Bank of America, this role defines and leads the engineering approach for complex features that deliver significant business outcomes. The Senior Engineer provides technical thought leadership, enables development efficiencies, applies broad and deep technical expertise, and is accountable for end-to-end solution design and delivery. The role architects the enterprise GenAI platform, defining reusable reference architectures and standards for GenAI use cases across model access, orchestration, retrieval, tool calling, agent patterns, and runtime controls. It establishes guidance for identity, data boundaries, guardrails, observability, resiliency, human oversight, high availability, fault tolerance, production performance, capacity, scaling, and service tiering. The engineer partners with platform engineering, security, architects, stakeholders, and use-case owners to ensure solutions align with enterprise standards and business outcomes, with clear responsibilities for developers, use-case owners, and end users. Bank of America supports an in-office culture for collaboration, engagement, and career development, with flexibility based on role responsibilities and business needs. The listed work locations are Jersey City, Pennington, and New York City. The role is first shift, 40 hours per week, and offers an annual salary range of $122,000 to $200,000. It is eligible for an annual discretionary incentive plan and benefits, including paid time off.

Requirements

10+ years in enterprise architecture, platform architecture, or distributed systems design.
Deep experience designing platforms operating at scale, rather than only single-use applications.
Strong experience with GenAI and agentic architecture, including model gateways, RAG, vector retrieval, orchestration, tool calling, guardrails, and evaluation.
Proven experience designing for high availability, scalability, and performance optimization.
Experience with capacity planning and workload distribution across distributed systems.
Experience defining standards for identity, access control, and secure service integration.
Experience defining data scope, governance, and controlled access in regulated environments.
Familiarity with observability, auditability, and resilience patterns.
Familiarity with telemetry, real-time monitoring and alerts, and traceability across distributed workflows.
Bachelor degree or equivalent professional experience.

Nice To Haves

Banking or other highly regulated enterprise environment experience.
Experience designing enterprise AI platforms that support multiple teams and products at scale.
Experience with AI model registries, lineage, and compliance metadata.
Experience with performance benchmarking and scaling strategies for AI workloads.
Experience with Agentic RAG and complex multi-hop retrieval patterns.
Experience with distributed, multi-agent systems operating under governance and control frameworks.

Responsibilities

Ensure the design and engineering approach for complex features is consistent with the larger portfolio solution.
Define the solution technology tool stack and evaluate and adapt testing tools, frameworks, and practices for teams.
Enable teams and applications with CI/CD capabilities and collaborate with technical stakeholders to support efficient CI/CD pipelines.
Guide and influence teams on design and high-performance coding practices, including pairing and code reviews.
Deliver complex features end to end, including automation, for one or multiple teams at program level.
Conduct research, design prototyping, and exploration of toolsets and components for release management, CI/CD, and features.
Work with stakeholders to establish high-level solution needs and with architects to establish technical requirements.
Define reference architecture for GenAI use cases across model access, orchestration, retrieval, tool calling, agent patterns, and runtime controls.
Produce architecture standards for identity, data boundaries, guardrails, observability, resiliency, and human-oversight patterns, including guidance for availability, fault tolerance, and production performance.
Establish capacity and scaling strategies for the platform.
Define resiliency architecture and service-tiering models.
Partner with platform engineering, security, and use-case owners to align solutions to approved GenAI patterns and business outcomes, with clear separation of responsibilities across Developer, Use Case Owner, and End User personas.