Software Engineer II at Bank of America

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 is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! Job Description: This job is responsible for developing and delivering complex requirements to accomplish business goals. Key responsibilities of the job include ensuring that software is developed to meet functional, non-functional and compliance requirements, coding solutions, unit testing, and ensuring the solution can be integrated successfully into the overall application/system with clear, robust, and well-tested interfaces. Job expectations include an awareness of development and testing practices in the industry. • The Senior Site Reliability Engineer (SRE) for the AI HPC Platform is responsible for ensuring the reliability, scalability, performance, security, and operational excellence of a large-scale AI and High-Performance Computing (HPC) environment. This role combines software engineering, systems administration, automation, and operational expertise to support AI/ML model development, training, inference, and production workloads running on GPU-based infrastructure. The engineer will drive platform stability through observability, automation, incident management, capacity planning, and continuous improvement initiatives. Responsibilities: • Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements • Utilizes multiple architectural components (across data, application, business) in design and development of client requirements • Performs Continuous Integration and Continuous Development (CI-CD) activities • Contributes to story refinement and definition of requirements • Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle • Contributes to existing test suites (integration, regression, performance), analyze test reports, identify any test issues/errors, and triage the underlying cause • Performs spike/proof of concept as necessary to mitigate risk or implement new ideas • Ensure the availability, reliability, scalability, and performance of AI HPC infrastructure supporting AI/ML training and inference workloads. • Administer and optimize Linux/Unix-based HPC environments, ensuring stable, secure, and efficient platform operations. • Manage and optimize SLURM workload scheduling, GPU resource allocation, queue management, and cluster utilization. • Design, implement, and maintain observability and monitoring solutions using Grafana and related technologies. • Support and administer OpenShift container platforms, ensuring reliable deployment and operation of AI services. • Manage PostgreSQL and Redis environments, including performance tuning, backup and recovery, and high-availability configurations. • Lead production incident response, root cause analysis, and problem management activities to improve platform resiliency. • Develop automation solutions, operational tooling, and Infrastructure-as-Code capabilities to enhance reliability and operational efficiency. • Perform capacity planning and performance management for GPU, compute, storage, and networking resources. Required Qualifications: • 5+ years of experience in Site Reliability Engineering, Infrastructure Engineering, Systems Engineering, or Platform Operations. • Strong expertise administering Linux and Unix operating systems in large-scale enterprise environments. • Hands-on experience with High Performance Computing (HPC) platforms. • Strong experience administering and troubleshooting SLURM workload managers. • Experience supporting Red Hat OpenShift and Kubernetes-based container platforms. • Deep understanding of monitoring and observability platforms, including Grafana. • Experience managing PostgreSQL databases in production environments. • Experience supporting Redis clusters and caching technologies. • Strong knowledge of networking, storage, security, and enterprise infrastructure concepts. • Experience with scripting and automation using Python, Bash, or similar languages. • Experience leading production incident response and root cause analysis. • Knowledge of high-availability architectures, disaster recovery, and resilience engineering practices. Desired Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent experience). • Experience supporting AI/ML, LLM, GPU, or GenAI platforms. • Experience managing NVIDIA GPU infrastructure, GPU operators, and AI workloads. • Familiarity with vLLM Inference Server, JupyterHub, or AI development platforms. • Experience with Infrastructure as Code tools such as Ansible, Terraform. • Experience with CI/CD pipelines and DevOps methodologies. • Knowledge of Prometheus, Elasticsearch, Loki, or other observability technologies. • Understanding of enterprise vulnerability management and regulatory compliance processes. • Experience working in highly regulated financial services or large enterprise environments. • Certifications such as: • Certified Kubernetes Administrator (CKA) • Red Hat OpenShift Administration Certification • Google SRE Certification • Red Hat Certified Engineer (RHCE) • AWS/Azure Cloud Certifications Skills: • Application Development • Automation • Collaboration • DevOps Practices • Solution Design • Agile Practices • Architecture • Result Orientation • Solution Delivery Process • User Experience Design • Unix/Shell Scripts Shift: 1st shift (United States of America) Hours Per Week: 40 Pay Transparency details US - NJ - Jersey City - 101 Hudson St - 101 Hudson (NJ2101) Pay and benefits information Pay range $88,800.00 - $144,800.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company. Benefits This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

Requirements

Must-haves

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Codes solutions and unit test to deliver a requirement/story per the defined acceptance criteria and compliance requirements
Utilizes multiple architectural components (across data, application, business) in design and development of client requirements
Performs Continuous Integration and Continuous Development (CI-CD) activities
Contributes to story refinement and definition of requirements
Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle
Contributes to existing test suites (integration, regression, performance), analyze test reports, identify any test issues/errors, and triage the underlying cause
Performs spike/proof of concept as necessary to mitigate risk or implement new ideas
Ensure the availability, reliability, scalability, and performance of AI HPC infrastructure supporting AI/ML training and inference workloads.
Administer and optimize Linux/Unix-based HPC environments, ensuring stable, secure, and efficient platform operations.
Manage and optimize SLURM workload scheduling, GPU resource allocation, queue management, and cluster utilization.
Design, implement, and maintain observability and monitoring solutions using Grafana and related technologies.
Support and administer OpenShift container platforms, ensuring reliable deployment and operation of AI services.
Manage PostgreSQL and Redis environments, including performance tuning, backup and recovery, and high-availability configurations.
Lead production incident response, root cause analysis, and problem management activities to improve platform resiliency.

Nice-to-haves

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent experience).
Experience supporting AI/ML, LLM, GPU, or GenAI platforms.
Experience managing NVIDIA GPU infrastructure, GPU operators, and AI workloads.
Familiarity with vLLM Inference Server, JupyterHub, or AI development platforms.
Experience with Infrastructure as Code tools such as Ansible, Terraform.
Experience with CI/CD pipelines and DevOps methodologies.
Knowledge of Prometheus, Elasticsearch, Loki, or other observability technologies.
Understanding of enterprise vulnerability management and regulatory compliance processes.
Experience working in highly regulated financial services or large enterprise environments.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlkubernetespythonllmci/cdawsazureagile

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Paid Time Off

Wellness