AI Engineer, Commercial Aircraft Group

Moog•Buffalo, NY

8d•Onsite

About The Position

Moog’s Commercial Aircraft Group is seeking an AI Engineer to join its technology team in an onsite role in Buffalo, New York. The position designs, develops, deploys, and supports artificial intelligence, generative AI, advanced analytics, intelligent agents, and automation solutions across engineering, manufacturing, operations, quality, and supply chain functions. The engineer builds scalable AI-powered solutions to improve productivity, streamline processes, support data-driven decisions, and deliver measurable business value in partnership with business and IT stakeholders. The role includes developing AI applications, copilots, agents, analytics, integrations, and automation; supporting proof-of-concept, pilot, and production implementations; and improving solution quality, performance, reliability, and business value. The engineer also supports testing, deployment, production readiness, issue resolution, user adoption, and ongoing enhancements. Solutions must meet enterprise cybersecurity, data governance, privacy, and Responsible AI requirements. The position contributes to engineering standards and best practices and provides technical guidance, documentation, training, and knowledge sharing across the Commercial Aircraft Group.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Software Engineering, Data Science, Information Systems, Engineering, or a related field.
Typically 3–7 years of combined experience in software development, solution engineering, automation development, data engineering, analytics, machine learning, artificial intelligence, or related technical disciplines.
Experience designing, developing, testing, and deploying enterprise applications and business solutions.
Knowledge of artificial intelligence, generative AI, large language models, machine learning, advanced analytics, and intelligent automation technologies.
Proficiency in one or more development languages such as Python, C#, JavaScript, or SQL, or similar technologies.
Experience integrating applications with enterprise systems, APIs, databases, and cloud-based platforms.
Understanding of data architecture, data modeling, data quality, and analytics principles.
Hands-on experience with Microsoft Azure, including DevOps, messaging systems, and Infrastructure as Code.
Practical knowledge of containerization technologies such as Docker, Kubernetes, and/or Azure Container Apps.
Understanding of distributed system architectures and design patterns.
Experience with REST APIs and testing tools such as Postman, Insomnia, or REST Client.
Experience with unit testing and integration testing.
Strong analytical and problem-solving skills and ability to translate business requirements into technical solutions.
Knowledge of cybersecurity, data governance, privacy, and Responsible AI concepts.
Experience working collaboratively with business stakeholders and cross-functional teams.
Strong communication skills, including the ability to explain technical concepts to technical and non-technical audiences.

Nice To Haves

Experience with Microsoft Copilot Studio, Microsoft Copilot, Power Platform, Azure AI Services, Azure OpenAI, Power Automate, and related technologies.
Familiarity with modern web technologies and frameworks such as React, Angular, or Vue.js.
Experience with Blazor Server or WebAssembly.
Experience with LLM orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, Semantic Memory, or similar technologies.
Experience supporting manufacturing, aerospace, engineering, supply chain, quality, or operations environments.
Experience building AI-powered copilots, intelligent agents, and conversational applications.
Experience developing Retrieval-Augmented Generation (RAG) solutions, knowledge retrieval systems, and semantic search capabilities.
Familiarity with ERP, MES, PLM, quality management, and manufacturing systems.
Knowledge of MLOps, prompt engineering, AI evaluation frameworks, and model governance practices.
Experience with Agile development methodologies and product-based delivery models.
Microsoft, Azure, AI, Power Platform, or software development certifications.

Responsibilities

Design, develop, test, deploy, and support AI-powered applications, intelligent agents, copilots, analytics solutions, and automation capabilities.
Partner with business stakeholders to understand requirements, identify opportunities, and translate business challenges into technical solutions.
Develop scalable, reusable AI-enabled capabilities aligned with enterprise architecture standards.
Build and maintain integrations between AI solutions, enterprise systems, data sources, and business applications.
Implement prompt engineering, grounding, retrieval, and orchestration techniques to improve AI solution quality and reliability.
Design and develop Microsoft Copilot, Copilot Studio, Azure OpenAI, and generative AI solutions for business and operational objectives.
Create and maintain enterprise copilots, agents, and conversational experiences that improve productivity and access to information.
Develop knowledge retrieval, search, and recommendation capabilities using enterprise content and data sources.
Support proof-of-concept, pilot, and production AI implementations.
Evaluate and optimize AI model performance, accuracy, usability, and business value.
Develop APIs, services, connectors, workflows, and integrations for AI-enabled business processes.
Integrate AI capabilities into existing business applications and digital platforms.
Collaborate with architects and developers to ensure solution scalability, maintainability, and performance.
Support system testing, user acceptance testing, deployment activities, and production readiness reviews; resolve technical issues and support enhancements.
Collaborate with data engineers and business teams to identify, prepare, and leverage data for AI initiatives.
Develop dashboards, reports, analytics, and data-driven insights to support business decision-making.
Evaluate emerging AI technologies, platforms, and capabilities for applicability within the Commercial Aircraft Group.
Identify opportunities to improve business processes through AI, automation, and advanced analytics.
Design and implement solutions that comply with enterprise cybersecurity, data governance, privacy, and Responsible AI requirements.
Partner with Cyber Security, Enterprise Architecture, Data Management, and Corporate AI teams to ensure compliance with established standards.
Support user adoption through demonstrations, documentation, training materials, and knowledge-sharing activities.
Provide technical guidance to business users, citizen developers, and AI champions.
Develop technical documentation, solution architectures, support procedures, and implementation guides.
Serve as a trusted technical advisor for AI-related initiatives and opportunities.
Contribute to AI engineering standards, development frameworks, and best practices.
Foster innovation, continuous learning, and responsible AI adoption across the Commercial Aircraft Group.

Benefits

Great compensation package
Annual profit sharing
Matching 401(k)
Employee Stock Purchase Plan
Flexible Spending and Health Savings Accounts
Flexible paid time off
Holidays
Parental leave program
Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability coverage
Employee Assistance Plan (EAP)
Supplemental benefit coverages
Tuition assistance
Mentorship and coaching opportunities
Leadership development and other personal growth programs
Employee Resource Groups
Site-specific benefits may also be available depending on location and business needs