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About This Role
This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Boston, MA; San Francisco Bay Area, CA; Dallas, TX; Salt Lake City, UT; Seattle, WA; and Portland, ME
About the Team/Role
We are seeking a seasoned Staff. Software Engineer in the WEX Mobility Engineering organization. This role will sit in the North America Mobility team that caters fleet management and mobility payments solutions to our large customers and partners in the North America region. Mobility development team spans across USA, Brazil, and India. Our Mobility systems provide SaaS and API solutions to various customers. WEX Mobility products enable credit issuance to fleet companies and their workers in the form of WEX or cobranded credit cards, usable at fueling stations and select other merchants. At WEX, we provide fleet managers and operators with fuel discounts, and flexibility to configure spend controls that restrict fleet members to use their cards at configured merchants, for configured amounts and velocity.
How you’ll make an impact:
- Design, develop, and maintain robust, scalable, and high\-performance object oriented code in our backend services.
- Develop public REST APIs using Java and internal gRPC APIs for inter\-service and inter\-system communication.
- Craft systems designs, lead design decisions, and drive alignment with other senior engineers.
- Write automated unit tests, integration tests, end\-to\-end tests, concurrency tests, load/performance tests.
- Analyze existing systems to identify bottlenecks, tech debt, and implement scalability, and stability improvements.
- Implement automation for testing, monitoring, healing, and scaling applications, continuous integration and deployment to reduce time to market
- Collaborate with cross\-functional teams, including product managers, designers, and other engineers, to define and implement new features.
- Conduct code reviews (comment, approve, seek revisions, merge), mentor junior and mid\-level engineers, and actively promote engineering best practices.
- Dive deep and troubleshoot complex issues, devise fixes, author root cause analysis documents, and ensure lasting performance and reliability.
- Conduct objective and comparative analyses of competing technologies to advise the team of pros and cons of a technology solution
- Maintain robust documentation (design docs, run books, change management docs, and readiness plans)
- Provide live\-site support for production applications by monitoring systems, ensuring rapid incident resolution, and driving continuous improvement.
- Drive cross\-team projects as a single\-threaded\-owner (STO) or tech lead, and actively unblock other engineers to make progress.
Experience you'll bring:
- Bachelor’s degree in Computer Science or Software Engineering
- 5\-8 years of professional experience in software engineering.
- Strong understanding of data structures and algorithms, object\-oriented design, and problem\-solving skills.
- Expertise in designing and developing internet\-scale services with scalability, availability, security, and reliability design tenets.
- Excellent written and verbal communication skills, and a collaborative and empathetic mindset.
- Proficiency in backend development, with proficiency expertise in Java or C\#, and frameworks like SpringBoot, building and optimizing RESTful APIs, ODATA framework, and SQL
- Ability to leverage AI\-enabled development tools such as Cursor AI, Kiro and GitHub Copilot to accelerate feature delivery, automate documentation, and enhance code quality.
Preferred Qualifications
- Master’s degree in computer science or software engineering.
- 10 years of experience in software engineering.
- Experience with event\-driven architecture and tools like Kafka.
- Experience working on card payments
- Familiarity with cloud\-native architecture (containerization using tools such as Docker and Kubernetes).
- Awareness of API security and PCI DSS compliance requirements
- Familiarity with mobile development (iOS or Android)
- Experience building AI skills \& deploying AI solutions to production environments
- Experience building production\-grade AI agents or copilots
- Familiarity with multi\-agent systems and distributed AI architectures
- Experience with vector databases (e.g., Pinecone, Weaviate, OpenSearch, Milvus)
- Knowledge of AI evaluation techniques, safety practices, and responsible AI principles
The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non\-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well\-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.
Pay Range: $140,600\.00 \- $173,100\.00
Salary Context
This $140K-$173K range is in the lower quartile 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 WEX Inc., 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. This role's midpoint ($156K) sits 32% below the category median. Disclosed range: $140K to $173K.
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.
WEX Inc. AI Hiring
WEX Inc. has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in Remote, US. Compensation range: $173K - $289K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% of all AI roles offer remote work.
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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