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About This Role
We take pride in what we do! Deciding to come grow with us is an exciting opportunity to enhance your career success stories. You are the center to what we do. We would love to have you here!
The Senior AI Software Engineer will play a leading role in the ground-up rewrite of Tower Loan’s loan origination and servicing platform, applying modern modular design principles, microservices, and event-driven architecture to support enterprise-scale deployment serving 1,000+ users across hundreds of locations. This role will champion an AI-first approach across requirements analysis, architecture, development, testing, and delivery.
This position combines strong full-stack engineering expertise in C#, .NET 10 or later, modern user interfaces, and SQL Server with practical experience using AI to accelerate development and embed intelligent capabilities into business workflows. Working closely with product, architecture, and engineering teams, this individual will help build a secure, scalable, and maintainable platform supporting the full lending lifecycle.
The ideal candidate brings strong engineering judgment, takes ownership of complex technical initiatives, and actively applies emerging AI capabilities while maintaining high standards for software quality, reliability, and security.* Design and develop Tower Loan’s next-generation loan origination and servicing platform using C#, .NET 10 or later, ASP.NET Core, SQL Server, and modern UI frameworks such as Blazor or React.
- Apply AI-first development practices throughout the software lifecycle, including requirements refinement, business rule extraction, architecture analysis, code generation, automated testing, refactoring, and documentation.
- Lead the technical design and delivery of complex features, translating business requirements into practical architecture, implementation plans, and reliable software.
- Design modular services with clear domain boundaries, reusable components, and well-defined APIs that support independent deployment, scalability, and maintainability.
- Implement event-driven communication and asynchronous processing using Kafka or comparable messaging technologies, with appropriate handling of retries, duplicate messages, failures, and data consistency.
- Engineer applications for enterprise-scale use across hundreds of locations, addressing concurrency, performance, resilience, and operational reliability.
- Analyze legacy .NET Framework applications to identify business rules, dependencies, and workflows, ensuring required functionality is accurately incorporated into the new platform.
- Support data migration, integration, and phased transition activities to maintain business continuity as the new platform replaces existing capabilities.
- Build responsive, accessible user interfaces that simplify loan origination, account servicing, payment processing, and other operational workflows.
- Design and optimize SQL Server schemas, stored procedures, views, queries, and indexes, emphasizing data integrity, transaction consistency, performance, and version control.
- Develop and integrate AI capabilities into business applications, including intelligent assistants, document processing, knowledge retrieval, and automated workflows.
- Build and maintain integrations with payment processors, document management and eSignature platforms, messaging services, analytics tools, and other internal and third-party systems.
- Independently review and validate AI-generated code and other outputs for correctness, security, performance, and maintainability.
- Implement appropriate controls for AI functionality, including access restrictions, sensitive data protection, output validation, evaluation, monitoring, and human review where warranted.
- Create and maintain automated tests, collaborate with QA, and validate that delivered functionality meets intended business outcomes and established quality expectations.
- Conduct code reviews, mentor other engineers, and contribute to engineering standards, architectural decisions, and continuous improvement.
- Troubleshoot complex application and distributed system issues using logging, metrics, and tracing to identify root causes and improve reliability.
- Contribute to CI/CD pipelines, deployment automation, technical documentation, data models, and API specifications.
- Implement security and privacy controls consistent with company policies and applicable regulatory requirements.
Perform all other duties as assigned. *
Required Skills/Abilities:
- Advanced proficiency in C# and modern .NET, including ASP.NET Core, API development, asynchronous programming, dependency injection, and application performance optimization.
- Strong full-stack development skills, including Blazor or React and supporting web technologies such as HTML, CSS, JavaScript, or TypeScript.
- Strong SQL Server development and troubleshooting skills, including relational data modeling, indexing, query optimization, and transaction management.
- Strong understanding of modular software design, microservices, REST APIs, event-driven architecture, domain-driven design, and clean architecture principles.
- Practical understanding of distributed systems, including service boundaries, asynchronous messaging, fault tolerance, idempotency, and eventual consistency.
- Ability to design applications for substantial concurrent usage and deployment across geographically distributed business locations.
- Demonstrated ability to use AI development tools effectively while maintaining ownership of technical decisions, code quality, testing, and delivered results.
- Practical understanding of large language model integration, prompt design, retrieval-augmented generation (RAG), tool calling, and the limitations of AI-generated output.
- Ability to extract and validate business rules from existing applications and translate them into clear requirements and maintainable implementations.
- Experience with automated testing, source control, code reviews, and CI/CD pipelines.
- Excellent debugging, analytical, and problem-solving skills, with the ability to evaluate technical tradeoffs and resolve complex issues.
- Ability to work independently, lead technical efforts, mentor teammates, and communicate effectively with technical and business stakeholders.
Demonstrated integrity, discretion, and professionalism when handling sensitive or confidential information. *
Education and Experience:
- Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field required.
- Five or more years of professional software development experience required, including substantial hands-on experience with C# and modern .NET.
- Demonstrated experience owning the design, development, testing, and delivery of complex enterprise applications required.
- Experience developing microservices and event-driven integrations in distributed application environments required.
- Experience developing user interfaces with Blazor or React required.
- Experience with SQL Server database development and performance tuning required.
- Demonstrated experience using AI tools within the software development lifecycle and integrating AI or large language model services into applications required.
- Proven experience integrating third-party APIs and developing internal services or reusable software components required.
- Experience with major application rewrites, platform modernization, or migration from legacy .NET Framework systems preferred.
- Experience supporting applications serving large user populations across multiple business locations preferred.
- Experience with Kafka, Redis, containerization, and cloud or private data center deployments preferred.
- Experience implementing AI evaluation, monitoring, and safeguards in production applications preferred.
- Experience with financial services, lending, loan origination, loan servicing, payment processing, or other regulated business systems preferred.
Relevant certifications in software development, AI, or cloud technologies preferred. *
Physical Requirements:
- Stand, walk, and/or sit for eight (8) hours a day
- Communicate effectively, verbally, written, in person, via telephone, or electronically.
Lift and maneuver up to 20 lbs. *
The above description outlines the most significant job functions performed, but may include other similar functions or assignments not explicitly mentioned.
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 8,943 AI roles we're tracking, AI Software Engineer positions make up 4% of the market. At Tower Loan, 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 $220,000 based on 1,448 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Tower Loan AI Hiring
Tower Loan has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Flowood, MS, US.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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