B
Senior Engineer - Senior AI Engineer
Bank of America
4 hours ago
Full-time
On-site
Charlotte, North Carolina, United States
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
#J-18808-Ljbffr
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
#J-18808-Ljbffr