Lead Software Engineer – Quantitative Investment Strategy, Agentic AI

🕒 5 days ago

🏢🏡 New York City – Hybrid

💵 $143k - $224k / year

⏰ Full Time

🟠 Senior

💸 Financial Planning and Analysis (FP&A)

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Wells Fargo

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1852

🏦 Banking

💸 Finance

🤝 B2B

Banking • Finance • B2B

Wells Fargo is a multinational financial services company recognized for its dedication to providing inclusive employment opportunities and fostering a supportive work culture. The company emphasizes diversity and inclusion across various dimensions, offering numerous early career programs and leadership development initiatives. Wells Fargo is renowned for enabling career growth through collaboration and innovation, ensuring its employees have a meaningful impact within a diverse workforce. With operations spanning numerous countries, the company is frequently highlighted as a leading employer, as evidenced by its placement on the LinkedIn Top Companies list.

📋 Description

• 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

• 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

• 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