Senior Engineer - Senior AI Engineer

Bank of America; Charlotte (NC); On-site; USD 150,000 - 210,000; Full time

Job summary

Bank of America is seeking a Senior AI Engineer to define and lead the engineering approach for complex features that deliver measurable business outcomes. You will design enterprise-grade AI agent solutions, integrate LLM platforms, and drive production-ready workflows across risk, finance and governance domains.

You will own end-to-end design, collaboration with architects and stakeholders, and apply prompt engineering, RAG patterns, and robust CI/CD practices to improve efficiency and enable

Qualifications

• 5–8+ years in software/AI solution engineering or data workflows
• Proven experience building AI agents/workflows with existing LLMs
• Hands-on experience with AI-assisted tooling like GitHub Copilot or Copilot Studio
• Strong understanding of RAG patterns, document ingestion, unstructured data
• Experience designing end-to-end AI workflows (prompting, retrieval, tool integration, validation)
• Proficiency in prompt engineering, grounding, and guardrails
• Strong Python skills and production-grade API development
• Experience with cloud-native architectures and enterprise integration
• Ability to define and measure outcomes and adoption metrics
• Strong stakeholder engagement to translate business problems into AI solutions

Responsibilities

• Ensures that the design and engineering approach for complex features aligns with the portfolio solution
• Define the technology stack for the solution and evaluate new testing practices
• Enable CI/CD capabilities and coordinate with stakeholders for efficient pipelines
• Guide teams on design and best practices for high code performance
• Deliver end-to-end complex features across one or multiple teams
• Conduct research, prototyping, and evaluate new tools for release management and CI/CD
• Collaborate with stakeholders to capture high-level solution needs and with architects for requirements
• Focus on integrating existing LLM platforms to build scalable AI agent systems

Skills

AI agent workflows

Python development

CI/CD practices

Prompt engineering

Stakeholder engagement

Cloud-native architectures

End-to-end AI design

Tools

GitHub Copilot

Copilot Studio

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 Description

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.

The Senior AI Engineer will design and deliver enterprise-grade AI agent solutions that automate document ingestion, orchestrate workflows, and augment decision-making across risk, finance, and governance domains. This role focuses on leveraging and integrating existing LLM platforms to build scalable, production-ready agent systems-embedding AI into engineering and product delivery workflows without developing foundational models. The role requires strong system design, agent orchestration, and pragmatic application of AI to drive measurable operational efficiency.

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
• This role focuses on leveraging and integrating existing LLM platforms to build scalable, production-ready agent systems-embedding AI into engineering and product delivery workflows without developing foundational models. The role requires strong system design, agent orchestration, and pragmatic application of AI to drive measurable operational efficiency.

Required Qualifications

• 5-8+ years of experience in software engineering, AI solution engineering, or applied data workflows (
• Proven experience building AI agents or agentic workflows using existing LLMs (task orchestration, tool use, memory, workflow chaining)
• Hands-on experience with AI-assisted development tooling (e.g., "GitHub Copilot", "Copilot Studio", or equivalent) to accelerate engineering productivity and solution design
• Strong understanding of RAG patterns , document ingestion, and unstructured data processing
• Experience designing end-to-end AI workflows (prompting, retrieval, tool integration, output validation)
• Proficiency in prompt engineering, grounding, and guardrails to ensure reliability and control
• Strong Python engineering skills and experience building production-grade services and APIs
• Experience with cloud-native architectures and integration into enterprise environments and tooling
• Ability to define and measure outcomes (efficiency gains, cost reduction, adoption metrics)
• Strong stakeholder engagement skills and ability to translate business problems into pragmatic AI solutions

Desired Qualifications

• Experience designing multi-agent or orchestrated agent systems for enterprise workflows
• Experience building interactive copilots or embedded AI assistants within engineering or operational tools
• Familiarity with agent evaluation techniques , human-in-the-loop validation, and iterative improvement loops
• Experience applying AI to workflow automation, operational efficiency, or service delivery transformation
• Knowledge of Responsible AI, governance, and enterprise risk considerations
• Track record of driving AI adoption across engineering or product organizations