ADS AI Services Software Engineer

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!

Position Summary:

This role is responsible for designing developing and operating containerbased application platforms that support Generative AI and Large Language Model (LLM) workloads at enterprise scale. The engineer will partner closely with application developers data scientists and platform teams to ensure AI workloads are deployed securely efficiently and reliably across Kubernetesbased environments.

The successful candidate will focus on building and managing GPUaccelerated containerized services enabling scalable inference platforms and supporting productiongrade AI frameworks. This role operates within a largescale enterprise environment and contributes to Agile delivery DevOps automation and continuous platform improvement.

Key responsibilities include:

• Designing deploying and maintaining containerized applications on Kubernetes and OpenShift platforms.
• Supporting Generative AI inference environments including model packaging deployment scaling and performance optimization.
• Enabling GPUbased workloads and ensuring efficient resource utilization and isolation.
• Collaborating with crossfunctional teams to deliver secure resilient and productionready AI platforms.
• Contributing to CI/CD pipelines infrastructure automation and operational best practices.
• Participating in Agile ceremonies and supporting iterative highquality software delivery.

Required Skills:

• 8 years in a technology environment with 5 years of experience with container tools
• Strong handson experience with Kubernetes including OpenShift and container tools such as Docker and Podman.
• Deep understanding of container orchestration concepts including scheduling networking storage configuration and secrets management.
• Experience operating container platforms supporting GPUaccelerated workloads.

• Proficiency in Python for developing and operationalizing AIdriven applications.
• Handson experience with Large Language Models (LLMs) and inferencefocused frameworks including:
  • vLLM
  • NVIDIA Triton Inference Server
  • NVIDIA NeMo framework
• Understanding of AI workload patterns including realtime and batch inference scaling strategies and highthroughput serving.

• Experience working in largescale enterprise environments with strong requirements for security reliability and compliance.
• Familiarity with CI/CD pipelines and DevOps practices for containerized applications.
• Experience contributing within Agile frameworks (Scrum Kanban or SAFe).
• Working knowledge of infrastructureascode and automated deployment approaches.

• Strong problemsolving skills and ability to troubleshoot complex platform issues.
• Clear concise communication with technical and nontechnical stakeholders.
• Ability to work effectively across engineering infrastructure security and data science teams.

Desired Skills:

• Experience operating container platforms in regulated or highly secure environments.
• Exposure to observability tools (logging metrics tracing) for distributed and AIdriven systems.
• Experience supporting multitenant platforms or shared AI inference services at scale.

Skills:

• Application Development
• Automation
• Collaboration
• DevOps Practices
• Solution Design
• Agile Practices
• Architecture
• Result Orientation
• Solution Delivery Process
• User Experience Design
• Analytical Thinking
• Data Management
• Risk Management
• Technical Strategy Development
• Test Engineering

Shift:

Hours Per Week: