Quantitative Engineer

Bank of America

. Design, develop, test, and implement common, reusable, and scalable software components .

Posted 9/18/2026full-timeCharlotte • New Jersey • United StatesJuniorMid-Level💰 $90,000 - $155,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing scalable software components and analytical solutions, with a strong focus on Python programming, AI-enabled technologies, and data management in the context of risk management and banking processes.

Highest-signal resume keywords

Python ProgrammingAI-Enabled Solutions DevelopmentData Sourcing and AnalysisQuantitative AnalysisBanking Processes Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Development Lifecycle (SDLC)Testing FrameworksDesign PatternsPerformance OptimizationSQLAPIsDatabasesQuantitative MethodsBig-Data PipelinesGovernance and Security Controls

Soft Skills

Critical ThinkingEffective CommunicationStakeholder ManagementSound Judgment

Tools & Technologies

LLM PlatformsAgent FrameworksRAGMCP Patterns

Industry Keywords

Risk ManagementRegulatory RequirementsFinancial Data SchemasData FlowsResponsible AI Practices

Tech Stack

Tools & technologies

PythonSDLCSQL

About the role

Key responsibilities & impact

Design, develop, test, and implement common, reusable, and scalable software components
Enable Global Risk Management’s data and analytical capabilities
Apply quantitative methods to meet line-of-business, risk-management, and regulatory requirements
Understand financial data schemas, flows, sizes, issues, and controls
Build performant big-data pipelines
Deliver high-quality code for model and testing processes using software development lifecycle principles
Collaborate with modelers, risk managers, technologists, process owners, data owners, Front Line Units, and Technology teams
Assess current-state processes, data, flows, and risks and design future-state technology solutions
Develop and deploy scalable analytical solutions using traditional and AI-based approaches
Source, validate, and analyze large and complex datasets
Implement governance, security, observability, and auditability controls for AI-enabled solutions
Monitor performance, optimize processes, and enhance solution effectiveness through testing, feedback loops, automation, and responsible AI adoption
Build subject matter expertise in bank processes, underlying data, flows, and controls

Requirements

What you’ll need

Bachelor’s degree or above in Mathematics, Computer Science, Statistics, Process and Mechanical Engineering, Operations Research, Data Science, or equivalent work experience
At least 2 years of relevant experience in software engineering in Quantitative Finance or other industries
Proficiency in Python and software development best practices
Knowledge of SDLC, testing frameworks, design patterns, and performance optimization
Experience developing AI-enabled solutions using modern LLM platforms, agent frameworks, RAG, and MCP patterns
Strong experience with structured and unstructured data, SQL, APIs, and databases
Experience with data sourcing, analysis, and integration at scale
Knowledge of responsible AI practices, AI performance monitoring, testing, reliability measurement, and scalability assessment
Knowledge of banking processes, risk management principles, and regulatory requirements
Critical thinking, quantitative analysis, and sound judgment
Effective communication and stakeholder management skills
Ability to work 40 hours per week on 1st shift in the United States of America

Benefits

Comp & perks

Affordable, competitive and flexible benefits
Support for physical, emotional, and financial wellness
Opportunities to learn, grow, and make an impact
Annual discretionary incentive plan eligibility
Paid time off
Resources and support to employees