Senior Cloud Engineer - GenAI Platform Engineering

Bank of America

Jersey City (NJ)

On-site

USD 140,000 - 210,000

Full time

5 hours ago

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Job summary

Bank of America is seeking a senior GenAI Platform Engineer to lead the engineering approach for complex features and end-to-end delivery of cloud-based solutions. This role focuses on scalable architectures, CI/CD, and platform reliability across multi-cloud environments.

Located in the United States (NJ/NY area), you will collaborate with Global Markets GenAI Technology, platform teams, and stakeholders to enable secure, scalable agent-based applications and model serving workloads.

Qualifications

7+ years in cloud engineering, platform engineering, or DevOps/SRE roles.
Hands-on experience with AWS, Azure, and/or GCP (multi-cloud preferred).
Experience with container platforms (Kubernetes, EKS, AKS, GKE) and IaC/CI/CD.

Responsibilities

Define the engineering approach for complex features to deliver business outcomes.
Lead end-to-end design and delivery, including CI/CD pipelines.
Build and operate the cloud infrastructure layer across AWS, Azure, and GCP.

Skills

Cloud engineering

DevOps / SRE

CI/CD pipelines

Kubernetes

Multi-cloud (AWS/Azure/GCP)

Observability / monitoring

Education

Bachelor's degree or equivalent experience

Tools

Terraform

Docker

CI/CD tooling

EKS

AKS

GKE

Job description

Job Description

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role‑specific responsibilities and business needs.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Responsibilities Overview

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.

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

Job Profile Summary

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.

Required Qualifications

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)

Desired Qualifications

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