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About This Role
Progressive Leasing is a leading provider of in-store and e-commerce lease-to-own solutions. With more than 20 years in FinTech, we’ve grown from start-up to industry leader by innovating, simplifying, and valuing people. We are a subsidiary of PROG Holdings (NYSE: PRG), a FinTech holding company with three business segments: Progressive Leasing, Purchasing Power (a leading employee purchase program for consumer products and services using payroll deduction), and Four, a Buy Now Pay Later (BNPL) platform.
We are currently hiring a Software Engineering Manager – .NET, Email/SMS Platforms to help grow our company and ensure our mission is achieved!
This role is a work from home position and can be performed remotely anywhere in the continental US or in our corporate location in Utah.
Employee Value Proposition (EVP): PROG is dedicated to providing people with opportunity; opportunity for inclusive collaboration, opportunity for innovation, and opportunity for development.
WE ARE: Prog Tech embodies the modernity and transformational vision that is core to our business evolution. As passionate and hungry technical experts, we progress through technology. We take pride in our engineering, daily progress, and bringing others along as we improve. We experiment, fail fast, and drive to delivery.
YOU ARE: A hands-on Technical Manager that will lead the engineering team that powers all customer communications email, SMS, and push notifications. You’ll spend part of your time designing and writing code in .NET, and the rest leading a small team to build reliable, compliant, and scalable messaging services. You’ll partner closely with Marketing, Product, Compliance to deliver the right message, on the right channel, at the right time.
YOUR DAY-TO-DAY:
Lead & code: Own technical direction while contributing code (design, implementation, code reviews) across .NET services, APIs, and orchestration workflows.
Cloud & containers: Drive cloud-native designs (e.g., AWS), containerization (Docker/Kubernetes), and CI/CD pipelines and automated testing.
Deliverability & reliability: Monitor and improve throughput, latency, bounce/complaint rates, inbox placement, and on-call practices.
Integrations: Manage integrations with ESPs/SMS gateways and internal systems
People leadership: Coach and develop engineers, set goals and hire to scale the team.
Incident management: Lead root-cause analysis, postmortems, and preventive engineering for capacity, deliverability, and provider issues.
YOU'LL BRING:
3+ years of engineering management experience leading software engineers (performance, hiring, coaching, delivery).
Strong hands-on .NET development experience
Cloud experience (AWS) designing and operating production systems.
Containerization & orchestration (Docker, Kubernetes) and CI/CD (Git-based workflows, pipelines, artifact/versioning).
Experience building/operating high-throughput, event-driven services (queues, pub/sub).
Solid grasp of observability (metrics, logs, traces) and production support (on-call, SLOs).
Salesforce Marketing Cloud (SFMC) knowledge is a plus
WE OFFER:
Competitive Compensation
Full Health Benefits; Medical/Dental/Vision/Life Insurance + Paid Parental Leave
Company Matched 401k
Paid Time Off + Paid Holidays + Paid Volunteer Time
Diversity Alliance Resource Groups
Employee Stock Purchase Program
Tuition Reimbursement
Charitable Gift Matching
Job Required Equipment & Services Will Be Provided
Progressive Leasing welcomes and encourages diversity in the workplace. We do not discriminate in any aspect of employment on the basis of race, color, religion, national origin, ancestry, gender, sexual orientation, gender identity and/or expression, age, veteran status, disability, or any other characteristic protected by federal, state, or local employment discrimination laws where Progressive Leasing does business.
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 37,339 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At Progressive Leasing, 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 $252,000 based on 337 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Progressive Leasing AI Hiring
Progressive Leasing has 1 open AI role right now. They're hiring across AI Software Engineer. Based in GA, US.
Remote Work Context
Remote AI roles pay a median of $160,000 across 1,226 positions. About 7% 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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