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About This Role
Moog is a performance culture that empowers people to achieve great things. Our people enjoy solving interesting technical challenges in a culture where everyone trusts each other to do the right thing. For you, working with us can mean deeper job satisfaction, better rewards, and a great quality of life inside and outside of work.
Job Title :
AI Software Engineer Reporting To:
Engineer, Chief Project Work Schedule:
Hybrid – Buffalo, NY We are seeking an experienced AI Software Engineer to join our team and contribute to the development and maintenance of our distributed cloud-based systems. The ideal candidate will have strong object-oriented programming skills, expertise in the .NET ecosystem, with hands-on experience in modern cloud technologies and containerization.
This role offers the opportunity to work at the intersection of traditional software engineering and emerging AI technologies, where your contributions will directly impact system performance, scalability, and innovation.
To be considered for the AI Software Engineer role, here’s what you’ll typically need to bring with you:
- Five (5) years of professional software development experience
- Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent professional experience
- Strong proficiency in C# and object-oriented programming (OOP) principles
- Proven experience with .NET framework and .NET Core
- Familiarity with modern web technologies and frameworks (React, Angular, Vue.js, etc.)
- Hands-on experience with Microsoft Azure including DevOps, Messaging Systems, and Infrastructure as Code
- Preferred experience with Blazor (Server or WebAssembly)
- Preferred experience with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel, Semantic Memory, or similar)
- Practical knowledge of containerization technologies (Docker, Kubernetes, and/or Azure Container Apps)
- Understanding of distributed system architectures and design patterns
- Experience with REST API and testing tools (Postman, Insomnia, REST Client, etc.)
- Experience with unit testing and integration testing
As a AI Software Engineer, you will:
- Design, develop, and maintain full stack applications using C# and .NET framework
- Build and enhance functionality for distributed cloud-based systems running on Azure
- Implement new business logic and features to support evolving system requirements
- Integrate and optimize generative AI and LLM capabilities into applications using orchestration frameworks
- Containerize applications using Docker, Kubernetes, and/or Azure Container Apps
- Support and troubleshoot existing production systems to ensure high availability
- Collaborate with cross-functional teams to deliver scalable and reliable solutions
- Write clean, maintainable, and well-documented code following OOP principles
- Participate in code reviews and contribute to continuous improvement initiatives
How We Care for You:
- Financial Rewards: great compensation package, annual profit sharing, matching 401k, and the ability to participate in Employee Stock Purchase Plan, Flexible Spending and Health Savings Accounts
- Work/Life Balance: Flexible paid time off, holidays and parental leave program, relocation assistance.
- Health & Welfare: Comprehensive insurance coverage including medical, dental, vision, life, disability, Employee Assistance Plan (“EAP”) and other supplemental benefit coverages.
- Professional Skills Development: Tuition Assistance, mentorship and coaching opportunities, leadership development and other personal growth programs
- Diverse and Inclusive Workplace: Employee Resource Groups, cultural events, and celebrations.
Salary Range Transparency:
Buffalo, NY $110,000.00–$145,000.00 Annually
Salary Range Disclaimer
The base salary range represents the low and high end of the Moog salary range for this position in the given work location. Actual salaries will vary depending on factors including but not limited to location, experience, and performance. The range(s) listed is just one component of Moog's total compensation package for employees. Other rewards may include annual bonuses, employee stock purchase plan, an open paid time off policy, and many region-specific benefits.
This position requires access to U.S. export-controlled information.
Moog offers an inclusive workplace, and, as such, affirms the right of every person to participate in all aspects of employment based on merit without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, age, veteran status, disability, genetic information, or any other protected characteristic. If you are interested in applying for employment and need special assistance or an accommodation to apply for a posted position, contact our Human Resources department via phone at 844-367-5787.
No unsolicited agency submittals please. Agency partners must be invited to participate in a search by our Talent Acquisition Team and have signed terms in place prior to any submittal. Absent compliance with these pre-conditions resumes submitted directly to any Moog Inc. employee or affiliate will not qualify for fee payment, and therefore become the property of Moog Inc.
Salary Context
This $110K-$145K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 146 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 8,943 AI roles we're tracking, AI Software Engineer positions make up 4% of the market. At Moog, 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 $220,000 based on 1,448 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($127K) sits 42% below the category median. Disclosed range: $110K to $145K.
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.
Moog, Inc AI Hiring
Moog, Inc has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Buffalo, NY, US. Compensation range: $145K - $145K.
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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