Senior Cloud Engineer - Genai Platform Engineering

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

This role is responsible for building and operating the cloud infrastructure layer for a Generative AI platform, enabling secure and scalable deployment of agent-based applications, APIs, and model-serving workloads. The role involves designing and managing containerized environments, developing deployment pipelines, and engineering scalable cloud architectures across AWS, Azure, and GCP.

What you'd actually do

  1. Build and operate the cloud infrastructure layer for the GenAI platform across AWS, Azure, and GCP, enabling secure and scalable deployment of agent-based applications, APIs, and model-serving workloads.
  2. Design, implement, and manage containerized environments (Kubernetes and managed services such as EKS, AKS, GKE)
  3. Develop and maintain scalable deployment and release pipelines
  4. Engineer highly scalable cloud architectures
  5. Ensures that the design and engineering approach for complex features are consistent with the larger portfolio solution

Skills

Required

  • 7+ years in cloud engineering, platform engineering, or DevOps/SRE roles
  • AWS, Azure, and/or GCP (multi-cloud experience preferred)
  • container platforms (Kubernetes, EKS, AKS, GKE)
  • infrastructure-as-code and CI/CD pipelines
  • highly scalable distributed systems
  • containerized workloads in production cloud environments
  • scaling strategies (autoscaling, load balancing, horizontal scaling)
  • performance tuning and system optimization
  • cloud-native architectures and microservices
  • observability tools (metrics, logging, distributed tracing)
  • reliability engineering (high availability, fault tolerance, disaster recovery)

Nice to have

  • Experience supporting AI/ML or GenAI workloads, including: model inference endpoints and API gateways, high-throughput, low-latency serving systems
  • Familiarity with vector databases, data pipelines, or retrieval-based architectures
  • scaling patterns for compute-intensive workloads
  • Experience in regulated enterprise environments (financial services preferred)
  • shared, multi-tenant platform environments supporting multiple teams

What the JD emphasized

  • GenAI Platform Engineering
  • agent-based applications
  • model-serving workloads
  • highly scalable distributed systems
  • highly scalable cloud architectures

Other signals

  • GenAI Platform Engineering
  • build and operate the cloud infrastructure layer for the GenAI platform
  • deployment of agent-based applications, APIs, and model-serving workloads
  • Develop and maintain scalable deployment and release pipelines
  • Engineer highly scalable cloud architectures