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Python Back information
Can I do backend in Python?
Are Python still in demand in 2026?
Is Python in demand for backend?
What is a Python Backend Developer?
What are the key skills and qualifications needed to thrive as a Python Backend Developer, and why are they important?
What jobs can I do with just Python?
What is the difference between Python Back and Python Data Engineer?
| Aspect | Python Back | Python Data Engineer |
|---|---|---|
| Required Credentials | Python programming, basic database knowledge | Python, SQL, data modeling certifications |
| Work Environment | Backend development teams, software companies | Data teams, analytics departments |
| Industry Usage | Software development, web services | Data analysis, big data projects |
| Common Search Intent | Backend development with Python | Data pipeline and infrastructure roles |
Python Back focuses on backend development tasks using Python, such as server-side logic and API creation. Python Data Engineer specializes in building data pipelines, managing data storage, and working with large datasets. While both roles require Python skills, Python Data Engineers often need additional knowledge of SQL and data architecture. Understanding these differences helps job seekers target the right roles based on their skills and career goals.
What are some common challenges Python Backend Developers face when optimizing application performance?

Lead Software Engineer - Quantitative Investment Strategy (QIS) & Agentic AI
Wells FargoIselin, NJ • On-site
Full-time
Medical, Life, Retirement, PTO
Posted 13 days ago
Wells Fargo rating
7.8
Based on 686 frontline employees who took The Breakroom Quiz
66th of 141 rated banks
Job description
About the
Wells Fargo is seeking a Lead Software Engineer - Quantitative Investment Strategy (QIS) & Agentic AI to join the Equity Derivatives Technology organization within Commercial and Corporate & Investment Banking. This role is central to the front-office risk and pricing platform, driving QIS index development, back testing, and risk analytics across equity derivatives.
You will lead the design and development of scalable, low-latency platforms supporting index construction, historical back testing, and real-time risk analytics for structured derivatives and trading desks. This is a hands-on senior role requiring strong expertise in distributed systems, Java, and Python-based quantitative workflows.
The role also integrates Agentic AI and GenAI capabilities to enhance automation, anomaly detection, and decision support. This is an opportunity to shape next-generation AI-enabled risk and trading platforms at scale.
In this role, you will:
- 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.
Required Qualifications:
- 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 AIassisted coding tools (e.g., GitHub Copilot) and contemporary IDEs
Desired Qualifications:
- Bachelor's degree or higher in Computer Science, Applied Mathematics, Financial Engineering, or a related field
- Demonstrated experience developing or integrating GenAI solutions, including LLMbased or agentic systems, applied to risk analytics, decision support, anomaly detection, or surveillance
- Strong experience in capital markets workflows, including trade capture, lifecycle management, pricing, and risk analytics, with handson exposure to equity derivatives products (options, futures, swaps, exotics, synthetics, convertibles, prime brokerage)
- Deep understanding of derivative pricing, valuation, and risk methodologies, including Greeks, VaR, CCAR, FRTB, DV01, and PnL attribution
- Proven ability to design, build, or integrate scalable frontoffice risk and analytics components with trading platforms
- Strong software engineering fundamentals: algorithms, data structures, performance optimization, clean code, and scalable system design
- Effective communicator able to work directly with frontoffice and business stakeholders in fastpaced, highpressure environments
Job Expectations:
This position is not eligible for Visa sponsorship
Relocation assistance is not available for this position
Position offers a hybrid work schedule
Location:
- 150 E 42nd St. - New York, NY 10017
- Metro Park, 194 Wood Avenue
Pay Range
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
$143,000.00 - $224,000.00Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. VisitBenefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
- 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
Posting End Date:
27 Jun 2026*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visitDisability Inclusion at Wells Fargo.
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.
What Wells Fargo employees say
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Get the full story on Breakroom
About Wells Fargo
Sourced by ZipRecruiter
Wells Fargo & Company (NYSE: WFC) is a leading financial services company that has approximately $1.9 trillion in assets, proudly serves one in three U.S. households and more than 10% of small businesses in the U.S., and is a leading middle market banking provider in the U.S. We provide a diversified set of banking, investment and mortgage products and services, as well as consumer and commercial finance, through our four reportable operating segments: Consumer Banking and Lending, Commercial Banking, Corporate and Investment Banking, and Wealth & Investment Management. Wells Fargo ranked No. 41 on Fortune's 2022 rankings of America's largest corporations. In the communities we serve, the company focuses its social impact on building a sustainable, inclusive future for all by supporting housing affordability, small business growth, financial health and a low-carbon economy.
Industry
Finance and insurance
Company size
10,000+ Employees
Headquarters location
San Francisco, CA, US
Year founded
1852