Quantitative Engineer

Bank of America

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

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

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable software components and analytical solutions, with a strong focus on quantitative methods, data management, and AI-enabled technologies. Proficient in Python and experienced in applying software development lifecycle principles to optimize performance and ensure compliance with risk management and regulatory standards.

Highest-signal resume keywords

Python ProficiencySoftware Development Lifecycle (SDLC)AI-Enabled Solutions DevelopmentData Sourcing and AnalysisRisk Management Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quantitative AnalysisBig Data Pipeline DevelopmentSQLAPIsTesting FrameworksPerformance OptimizationData IntegrationDesign PatternsGovernance ControlsContinuous Optimization

Soft Skills

Critical ThinkingSound JudgmentStrong CommunicationStakeholder Management

Tools & Technologies

LLM PlatformsAgent FrameworksRAG PatternsMCP Patterns

Industry Keywords

Financial Data SchemasRisk ManagementRegulatory RequirementsResponsible AI PracticesData Science

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 technical solutions
Design, build, document, and deploy scalable analytical solutions using software engineering, big data, data science, risk management, and AI patterns
Source, validate, and analyze large and complex datasets
Implement governance, security, observability, and auditability controls for AI-enabled solutions
Monitor performance, drive process optimization, and enhance solution effectiveness through testing, feedback loops, automation, and responsible AI adoption

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 solution performance monitoring, testing, reliability measurement, scalability assessments, and continuous optimization
Knowledge of banking processes, risk management principles, and regulatory requirements
Critical thinking, quantitative analysis, and sound judgment
Strong communication and stakeholder management skills

Benefits

Comp & perks

Annual discretionary incentive plan eligibility
Benefits eligibility
Paid time off
Resources and support for employees
Flexible benefits supporting physical, emotional, and financial wellness
In-office culture supporting collaboration, engagement, and career development
Opportunities to learn, grow, and make an impact