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About This Role
Job Title:
Principal Engineer I \- AI Full Stack EngineerLocation:
Block 23What you'll do:
As a Principal Engineer I, you will serve as a senior technical contributor within your domain, applying deep expertise across multiple engineering disciplines to design and deliver complex solutions. This role is embedded within the Lending and Card Operations technology teams, with a primary focus on supporting the Lending Service Fabric (LSF) through modern, AI enabled full stack solutions. In this role, you will partner closely with architects, product owners, and business stakeholders to translate requirements into secure, compliant, and scalable designs. You will apply AI forward engineering practices, guide technical implementation decisions, and help establish reusable patterns that improve delivery efficiency while aligning with WAB engineering and governance standards.* Provide senior‑level technical leadership for Lending and Card Operations initiatives, contributing to solution architecture and engineering decisions aligned to business and regulatory requirements.
- Design and deliver AI‑enabled, cloud‑native full‑stack solutions that support loan and card processing, servicing, operations, and reporting, ensuring scalability, security, and compliance.
- Design and implement AI‑forward capabilities, including Prompt Engineering, MCP, and RAG‑based patterns, under established architectural guidance to improve automation, decisioning, and developer productivity.
- Design, build, and maintain enterprise APIs using Azure API Management (APIM), ensuring consistent security, versioning, throttling, observability, and lifecycle management.
- Own assigned portions of end‑to‑end technical solution design, producing clear and executable designs that can be delivered by engineering teams while adhering to WAB architecture standards and reuse of enterprise capabilities.
- Lead hands‑on full‑stack development across Azure, .NET, Python, React (Vite), SQL, and ETL pipelines, following modern DevOps practices using GitHub, Azure DevOps, and Azure Pipelines.
- Apply AI‑assisted development practices (e.g., GitHub Copilot and approved internal LLMs) to improve development speed and code quality while adhering to governance and security controls.
- Contribute to observability, performance, and reliability practices to ensure Lending and Card systems meet operational, security, and audit requirements.
- Review technical designs, code, and delivery plans developed by engineers to ensure solutions meet performance, resilience, and compliance expectations.
- Partner with business, architecture, security, and risk teams to translate Lending and Card requirements into compliant technical solutions, communicating effectively with both technical and non‑technical stakeholders.
- Mentor engineers and promote adoption of AI‑forward, cloud‑first, and platform‑driven engineering practices within the Lending and Card Operations technology teams.
What you'll need:
- 8\+ years of experience in software engineering or IT development, with demonstrated experience supporting Lending, Card, or Financial Services platforms.
- Hands‑on experience designing and developing cloud‑native applications on the Azure platform, including APIs, data integrations, and full‑stack solutions.
- Practical experience applying AI‑assisted development techniques (e.g., Prompt Engineering, RAG patterns, or GenAI development tools) in an enterprise environment.
- Strong experience with .NET, Python, modern JavaScript frameworks (React preferred), SQL, and ETL technologies.
- Bachelor’s degree in a related field required; Master’s degree or MBA preferred.
- Previous technical leadership or lead‑engineer experience preferred.
- Advanced knowledge of Financial Services or Banking, with exposure to Lending or Card Operations strongly preferred.
- Working knowledge of regulatory and legal compliance obligations, industry standards, and secure software development practices in a regulated environment.
- Proven experience collaborating with cross‑functional teams and delivering multiple initiatives concurrently within an Agile or DevOps environment.
- Familiarity with enterprise capability models, IT governance frameworks, and architectural review processes.
- Strong verbal and written communication skills, with the ability to clearly explain technical concepts to business and technology stakeholders.
- May require up to 25% travel.
Benefits you’ll love:
We offer all the important things you'd want — like competitive salaries, an ownership stake in the company, medical and dental insurance, time off, a great 401k matching program, tuition assistance program, an employee volunteer program, and a wellness program. In addition, you’ll have the opportunity to bolster your business knowledge, learning the ins and outs of how successful companies operate and manage their finances, giving you invaluable hands\-on experience to help grow your career!
About the company:
Western Alliance Bank, Member FDIC, is a wholly owned subsidiary of Western Alliance Bancorporation. Serving clients nationwide, Western Alliance Bank includes six legacy bank brands — Alliance Association Bank, Alliance Bank of Arizona, Bank of Nevada, Bridge Bank, First Independent Bank and Torrey Pines Bank — that remain part of the company’s heritage, as well as AmeriHome Mortgage, a Western Alliance Bank Company.
Western Alliance Bancorporation is committed to equal employment and will consider all qualified applicants without regard to race, sex, color, religion, age, nation origin, marital status, disability, protected veteran status, sexual orientation, gender identity or genetic information. Western Alliance Bancorporation is committed to working with and providing reasonable accommodations for individuals with disabilities. If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process and/or need an alternative method of applying, please email [email protected] or call 602\-386\-2488\. When contacting us, please provide your contact information and state the nature of your accessibility issue. We will only respond to inquiries concerning requests that involve a reasonable accommodation in the application process.
© Western Alliance Bancorporation
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 Western Alliance Bank, 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.
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.
Western Alliance Bank AI Hiring
Western Alliance Bank has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Phoenix, AZ, US.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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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