Data Engineer II
Bank of America · Charlotte, NC
Skills in this posting
The posting
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 developing and delivering data solutions to accomplish technology and business goals and initiatives. Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems.
Job expectations include working with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.
Seeking an innovative and results-driven Generative AI & Agentic AI Engineer to design, develop, and deploy enterprise-scale AI solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation frameworks. This role is responsible for building secure, scalable, and governed AI applications that enhance productivity, automate business processes, and enable data-driven decision making across the organization.
Responsibilities
Works across development teams to contribute to the story refinement and delivery of data requirements through the delivery life cycle
Leverages architecture components in solution development, codes solutions to integrate, clean, transform, and control data in operational and analytical data systems per acceptance criteria
Builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management and defines and builds data pipelines and complex data sets to enable data-informed decision making, identi
fying and raising risks at all stages of the data engineering process
Develops and executes test plans to produce quantitative results, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and triages underlying causes
Drives complex information technology projects to ensure on-time delivery and adheres to team delivery and release processes
Identifies, defines, and documents data engineering requirements, communicating required information for deployment, maintenance, support, and business functionality
Works with technology partners and a diverse set of stakeholders to identify and close gaps in data management standards adherence, negotiates paths forward, and helps identify and communicate solutions to complex data problems leveraging knowledge of information systems, techniques, and processes
Design and implement Gen AI and Agentic AI solutions using LLMs, RAG, vector databases, and enterprise AI platforms.
Build and orchestrate AI agents capable of interacting with enterprise systems, APIs, tools, and knowledge repositories.
Develop scalable AI services, APIs, and microservices using cloud-native architectures.
Implement prompt engineering, retrieval optimization, guardrails, evaluation frameworks, and observability patterns.
Establish governance, security, privacy, and compliance controls for AI systems.
Collaborate with business stakeholders to identify and prioritize AI use cases:
Required Qualifications
Experience with Gen AI, LLMs, RAG, or AI agents in enterprise environments
3+ years or relevant experience
Bachelor's or Master's degree in one of the following
Computer Science
Artificial Intelligence
Data Science
Software Engineering
Machine Learning
Related STEM discipline
Skills
Analytical Thinking
Application Development
Data Management
DevOps Practices
Solution Design
Agile Practices
Collaboration
Decision Making
Risk Management
Test Engineering
Architecture
Business Acumen
Data Quality Management
Financial Management
Solution Delivery Process
Shift
1st shift (United States of America)
Hours Per Week
40
The PivotHop read
- What a data engineer actually earnsmedian, seniority, by country
- Where data engineers move nextevery measured route out
- Data Architect → Data Engineer47% readiness
- Data Analyst → Data Engineer31% readiness
- All open data engineer rolesthe full board
Where these skills also reach
- 74 open data architect roles91% readiness from data engineer
- 507 open data analyst roles63% readiness from data engineer
- 58 open database administrator roles59% readiness from data engineer
- 600 open solutions architect roles59% readiness from data engineer
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