Senior Cloud Engineer - GenAI Platform Engineering

Bank of America•New York, NY

1d•$122,000 - $200,000•Onsite

About The Position

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. Global Markets GenAI Technology is a fast-growing global team with locations in New York City, Charlotte, London, and India. Generative AI presents an exciting opportunity to derive valuable insights from data and drive revenue growth, efficiencies, and improved business processes. Global Markets GenAI Technology will collaborate with Global Markets Sales & Trading, Quantitative Strategies & Data Group (QSDG) & Platform teams to the design and buildout global generative AI platform. The platform will cater to a rapidly growing number of use cases that harness the power of Generative AI. Both proprietary and open-source Large Language Models, and large structured and un-structured data sets will be leveraged to produce insights for Global Markets and its clients.

Requirements

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

Nice To Haves

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

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
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.
Design, implement, and manage containerized environments (Kubernetes and managed services such as EKS, AKS, GKE)
Develop and maintain scalable deployment and release pipelines
Engineer highly scalable cloud architectures