Senior Engineer - Enterprise Genai Platform Architect

Bank of America Bank of America · Banking · New York, NY

Senior Engineer responsible for defining and leading the engineering approach for complex features, focusing on enterprise GenAI platform architecture. This role involves defining reference architectures, standards, and scaling strategies for GenAI use cases, including model access, orchestration, retrieval, tool calling, and agent patterns, ensuring scalability, reusability, and alignment with enterprise standards in a regulated environment.

What you'd actually do

  1. Define the reference architecture for GenAI use cases across model access, orchestration, retrieval, tool calling, agent patterns, and runtime controls, ensuring designs are scalable, reusable, and aligned to enterprise standards.
  2. Produce architecture standards covering identity, data boundaries, guardrails, observability, resiliency, and human-oversight patterns, with explicit guidance on designing for high availability, fault tolerance, and production-grade performance
  3. Establish capacity and scaling strategies for the platform
  4. Partner with platform engineering, security, and use-case owners to ensure new solutions align to approved GenAI patterns and business outcomes, with clear separation of responsibilities across Developer, Use Case Owner, and End User personas
  5. Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution

Skills

Required

  • enterprise architecture
  • platform architecture
  • distributed systems design
  • GenAI/agentic architecture
  • model gateways
  • RAG
  • vector retrieval
  • orchestration
  • tool calling
  • guardrails
  • evaluation
  • high availability
  • scalability
  • performance optimization
  • capacity planning
  • workload distribution
  • identity
  • access control
  • secure service integration
  • data scope
  • governance
  • controlled access
  • regulated environments
  • observability
  • auditability
  • resilience patterns
  • telemetry
  • real-time monitoring/alerts
  • traceability across distributed workflows

Nice to have

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

What the JD emphasized

  • Deep experience designing platforms operating at scale, not just single-use applications
  • Strong experience with GenAI/agentic architecture: model gateways, RAG, vector retrieval, orchestration, tool calling, guardrails, evaluation
  • Proven experience designing for: high availability, scalability, and performance optimization
  • Experience defining standards for: data scope, governance, and controlled access in regulated environments

Other signals

  • GenAI Platform Architecture
  • Scalable and Reusable Designs
  • Architecture Standards for GenAI Use Cases
  • Production-Grade Performance