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About This Role
About this role:
Wells Fargo is seeking a Lead Specialty Software Engineer in Technology as part of Commercial and Corporate \& Investment Banking Technology (CCIBT). This is an exciting opportunity to join the team building next‑generation solutions for the Wells Fargo Capital Markets Technology organization. We are seeking a Lead Specialty Data Engineer to play a key role in our automation, AI adoption, and platform modernization journey. If you are passionate about solving complex, mission‑critical problems using leading‑edge technologies, advanced analytics, and AI‑assisted engineering practices—grounded in strong software engineering fundamentals—this role is well suited for you.
In this role, you will help build and evolve strategic trading analytics data platforms, including the Low Touch Data Hub and the next‑generation Equities Data \& Analytics platform supporting all Equities Front Office trading groups. You will contribute to the design and delivery of scalable application frameworks and data services within Commercial and Corporate \& Investment Banking Technology, enabling advanced analytics, AI‑driven insights, and automation across the Equities trading lifecycle.
This role defines and governs enterprise‑standard AI‑assisted engineering patterns, including prompt‑driven development, automated testing, diagnostics, documentation, and developer‑productivity tooling. You will architect and guide controlled LLM integrations—such as MCP‑based services—across development workflows, observability, and automation, while establishing guardrails to ensure secure, explainable, auditable, and compliant AI usage within electronic trading technology. In partnership with platform, security, risk, and compliance teams, you will ensure AI‑enabled engineering practices meet Wells Fargo governance standards and continuously evaluate advances in GenAI, agentic AI, and applied ML to safely evolve engineering capabilities at enterprise scale.
This role supports a fast‑paced Front Office equity trading environment, delivering senior‑level software and analytics solutions for trading, automation, and decisioning. You will build AI‑enabled analytics platforms and low‑latency systems, apply AI‑centric engineering practices, and write high‑quality Java and Python code while partnering closely with traders, Strats, and quants. The role includes technical leadership, rigorous testing and reviews, production reliability ownership, and Level‑2 support for performance, data, and model‑driven issues.
Learn more about career areas and lines of business at wellsfargojobs.com.
In this role, you will
- Lead complex initiatives on selected domains
- Ensure systems are monitored to increase operational efficiency and managed to mitigate risk
- Define opportunities to maximize resource utilization and improve processes while reducing cost
- Lead, design, develop, test and implement applications and system components, tools and utilities, models, simulation, and analytics to manage complex business functions using sophisticated technologies
- Resolve coding, testing and escalated platform issues of a technically challenging nature
- Lead team to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives
- Mentor less experienced software engineers
- Collaborate and influence all levels of professionals including managers
- Lead team to achieve objectives
- Partner with production support and platform engineering teams effectively
Required qualifications
- 5\+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- 5\+ years of Software Engineering experience, with a strong focus on data‑intensive systems
- 5\+ years of experience building analytics platforms, data services, or data‑driven applications
- 5\+ years of experience with algorithms and data structures, particularly as applied to analytics and data processing
- 4\+ years of experience designing and implementing distributed data systems
- 4\+ years of experience with time‑series, relational, or analytical databases
- 4\+ years of experience in Java for building high‑performance backend and data services
- 4\+ years of experience in Python for analytics, data processing, and automation
Desired qualifications:
- Advanced experience in capital markets business processes
- Working knowledge of SEC, FINRA, and international regulatory considerations when building technology solutions
- Cash Equities and Global Markets trading workflow knowledge; FIX protocol experience
- Deep understanding of concurrency, memory management, and performance tuning in data‑heavy systems
- Experience with application lifecycle management from design through production support, including AI‑enabled or analytics‑driven systems
- Strong understanding of distributed and client‑server technology architectures
- Prior team lead and/or direct or matrix management experience
- Outstanding written and verbal communication skills appropriate for a Front Office environment
- BS/BA degree or higher
Job Expectations:
- This position is not eligible for Visa sponsorship
- Relocation assistance is not available for this position
- Position offers a hybrid work schedule
Posting Locations:
- 150 E 42nd St. New York, NY 10017
- 300 S Brevard St., Charlotte, NC 28202
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.
$159,000\.00 \- $305,000\.00Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits \- 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:
26 Jul 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, visit Disability 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.
Salary Context
This $159K-$305K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Wells Fargo, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 797 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $159K to $305K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Wells Fargo AI Hiring
Wells Fargo has 23 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Safety, AI Product Manager. Positions span Charlotte, NC, US, Chandler, AZ, US, Irving, TX, US. Compensation range: $140K - $305K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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