Infrastructure Engineer II

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 Description:

This job is responsible for tool and service designs within a technical domain that enable business strategies in accordance with architectural governance, standards and policies. Key responsibilities include creating infrastructure tools and their integration as a service, facilitating deployment of technical solutions by developing templates, playbooks and automation used during implementation. Job expectations include looking for opportunities to improve efficiency when implementing and maintaining tools/services and embracing a culture of innovation and continuous improvement.

 

We are seeking an experienced Kubernetes AI Engineer to design, build, and optimize enterprise-scale AI platform infrastructure that supports model development, training, and inference workloads. This role requires deep expertise in Kubernetes, containers, Linux, and platform engineering, with a strong focus on scalability, security, performance, observability, and automation. The ideal candidate will partner closely with AI/ML engineers, data scientists, DevOps teams, and infrastructure teams to deliver resilient, compliant, and high-performing AI platforms in complex enterprise environments.

 

Responsibilities:

• Provides subject matter expertise and consulting services on a range of technologies and assists Technical Analysts and Infrastructure Engineers to ensure that technology solutions comply with enterprise system design and engineering standards
• Assists with translating business requirements into technical definitions, reference models, blueprints, and playbooks for deployment in compliance with architecture standards and policies
• Assists in the evaluation of reference models, blueprints and playbooks to ensure they are fit for purpose
• Develop software solutions to address manual and repeatable work or inefficient processes
• Conducts on-site evaluations of third-party products being considered for firm adoption
• Promotes an inclusive and healthy working environment and helps to resolve organizational impediments/blockers
• Contributes to the creation/selection of functional and non-functional product evaluation requirements within and across domains

 

Required Qualifications:

• 5+ years of experience in Kubernetes, container platform engineering, Linux systems, or AI/ML infrastructure in enterprise environments.
• Design and engineer Kubernetes-based AI platform infrastructure for model development, training, inference, and supporting services.
• Build and manage containerized environments using Docker, Kubernetes, Operators, and Helm charts across development and non-development environments.
• Optimize cluster performance, workload placement, scalability, resiliency, and resource utilization for AI/ML workloads.
• Implement security and compliance controls including RBAC, network policies, pod security, secrets management, and enterprise standards.
• Establish observability through monitoring, logging, dashboards, and alerting using tools such as Prometheus and Grafana.
• Develop automation for deployment, configuration, patching, and operational workflows using Python, shell scripting, and infrastructure-as-code practices.
• Collaborate with AI/ML engineers, data scientists, DevOps, and infrastructure teams to translate business and technical requirements into scalable platform solutions.
• Create and maintain architecture documents, runbooks, standards, and operational procedures to support reliable platform delivery.
• Strong expertise in Kubernetes architecture, cluster deployment, orchestration, and lifecycle management.
• Hands-on experience with Docker, container runtimes, Operators, and Helm charts.
• Strong Linux administration and troubleshooting skills across compute, networking, and storage layers.
• Proficiency in Python, shell scripting, YAML, and JSON for automation and platform engineering.
• Experience with observability and monitoring tools such as Prometheus, Grafana, and logging frameworks.
• Knowledge of Kubernetes security practices including RBAC, network policies, pod security, secrets management, and vulnerability awareness.
• Experience supporting AI/ML platforms, model deployment pipelines, or GPU-enabled workloads in enterprise environments.
• Familiarity with CI/CD, GitOps, infrastructure automation, and environment standardization practices.
• Strong problem-solving and analytical thinking skills in complex, fast-paced environments.
• Clear written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.
• Collaborative mindset with experience working across AI/ML, DevOps, CTO, CIO, and infrastructure teams.
• Strong documentation discipline and attention to detail.
• Ability to balance strategic thinking with hands-on execution and delivery.
• Self-starter mindset with ownership, accountability, and continuous improvement orientation.

 

Desired Qualifications

• Kubernetes certifications such as CKA or CKAD.
• Understanding of Vulnerability Management, Non-Permitted Technology Remediations, Enterprise Controls
• Prior experience building agents and agentic AI solutions in enterprise
• Knowledge of Copilot Studio to build apps would be nice to have
• Experience with AI/ML frameworks and model-serving platforms such as PyTorch, TensorFlow, Triton, or vLLM.
• Familiarity with GPU platforms, NVIDIA software stack, or high-performance AI infrastructure.
• Experience with OpenShift, hybrid cloud, or enterprise platform modernization initiatives.

 

Skills:

• Analytical Thinking
• Application Development
• Automation
• Production Support
• Risk Management
• Adaptability
• Business Acumen
• DevOps Practices
• Solution Delivery Process
• Solution Design
• Architecture
• Collaboration
• Innovative Thinking
• Stakeholder Management
• Technical Strategy Development

 

Minimum Education Requirement: Bachelor’s degree or equivalent work experience.

 

Shift:

1st shift (United States of America)

Hours Per Week: 

40