Lead Software Engineer – Quantitative Investment Strategy, Agentic AI

Wells Fargo

Lead Software Engineer developing QIS and AI-driven platforms at Wells Fargo. Collaborating with front-office teams for scalable solutions in equity derivatives and risk analytics.

Posted 6/5/2026full-timeNew York City • New Jersey, New York • 🇺🇸 United StatesSenior💰 $143,000 - $224,000 per yearWebsite

Tech Stack

Tools & technologies

CassandraDistributed SystemsMongoDBNoSQLNumpyPandasPython

About the role

Key responsibilities & impact

Lead QIS platform engineering initiatives, partnering with front-office, quantitative research, and trading teams to deliver scalable solutions for index strategy development, back testing, and performance analytics.
Design and build QIS index lifecycle platforms, including index construction, rebalancing, corporate actions handling, and historical simulation/back testing frameworks across large-scale market datasets.
Develop Python-based quantitative workflows and analytics, enabling rapid prototyping, strategy validation, and automation of research-to-production pipelines.
Architect low-latency, distributed systems supporting real-time and intraday risk analytics, index recalculations, and portfolio-level risk aggregation under strict performance and resiliency requirements.
Integrate Agentic AI and GenAI capabilities into QIS and risk platforms for automation, anomaly detection, monitoring, and decision support, improving efficiency and insight generation.
Drive engineering excellence and platform reliability, including data quality controls, model validation support, observability, testing automation, and production readiness, while mentoring teams and ensuring compliance with risk and regulatory standards.

Requirements

What you’ll need

5+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of hands-on Python (or equivalent scripting) for time-series analytics, numerical computing (NumPy/Pandas), and research-to-production workflows
3+ years of experience in QIS index development, including index construction, rebalancing, corporate actions, and backtesting frameworks
3+ years designing distributed, low-latency systems supporting real-time or intraday analytics and large-scale market data processing
3+ years of equity derivatives / quantitative finance experience, including pricing models, Greeks, and portfolio risk analytics
2+ years working with AI/ML or GenAI systems, including LLM integration, automation, anomaly detection, or agent-based workflows
2+ years working with NoSQL databases such as MongoDB or Cassandra, including proficiency in handling massive datasets
1+ years of solid experience in modern AI development tooling, including AI‑assisted coding tools (e.g., GitHub Copilot) and contemporary IDEs

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement

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Hard Skills & Tools

Pythontime-series analyticsnumerical computingNumPyPandasQIS index developmentbacktesting frameworksdistributed systemsreal-time analyticsequity derivatives

Soft Skills

engineering excellencementoringcompliancedata quality controlsobservabilitytesting automationproduction readiness