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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - Agentic Solutions & Digital Thread - **Company:** Moog Inc. - **Location:** Buffalo, NY, United States - **Experience:** Expert - **Salary:** $135,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Agile Methodology, Artificial Intelligence, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Cloud Engineering, Code Generation, Data Governance, DevOps, Python (Programming Language), Software Architecture, SAP (Applications), Search Technologies, Software Engineering, TypeScript, Azure Service Bus, Data Classification, Large Language Models, Multi-Agent Systems, Event Driven Architecture, Infrastructure Automation Frameworks, Information Technology, Integration Frameworks, Apache Kafka, Data Management, Virtual Agents, Databricks, Teamcenter (Software) - **Published:** August 12, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17915437?backUrl=%2Fcareer%2F17915437%2FSenior-Ai-Engineer-Agentic-Solutions-Digital-Thread-New-York-Buffalo ## About the Role * Typically, a bachelor's degree in computer science, Software Engineering, AI/ML, or equivalent experience. * 8+ years of professional software development, with 3+ years focused on AI/ML solution development. * Hands-on experience with agentic AI frameworks (Semantic Kernel, AutoGen, LangChain/LangGraph, CrewAI, or equivalent), MCP (Model Context Protocol), multi-agent orchestration, and secure tool integration patterns. * Demonstrated experience designing and implementing advanced RAG architectures, including vector databases, embedding models, retrieval strategies, and Context Engineering techniques to ground AI responses in enterprise knowledge. * Strong communication and collaboration skills with technical and non-technical stakeholders. * Proficiency in Python and at least one additional language (C#, .NET, or TypeScript). * Strong experience with Microsoft Azure services and cloud-native architectures. * Experience with CI/CD pipelines, Infrastructure as Code, automated testing, and Agile/DevOps delivery. * Experience with Databricks, lakehouse architectures, and enterprise data integration patterns. * Experience with event-driven architectures and integration platforms (Azure Service Bus, Event Grid, Kafka). * Exposure to MDM, data governance, data quality frameworks, or rules-based systems. * Exposure to digital thread concepts in manufacturing, including PLM (Teamcenter), ERP (SAP), MES, and QMS integration. * Experience in aerospace, defense, or regulated manufacturing environments (ITAR, EAR, CMMC, DFARS). * Familiarity with AI governance frameworks (e.g., NIST AI RMF) and responsible AI practices. * Azure certifications (Azure AI Engineer, Azure Solutions Architect) are a plus. ## Description The role serves as the lead developer for assigned AI and agentic solution use cases, translating business requirements into scalable, auditable, and explainable implementations aligned to enterprise Digital Thread, Master Data Management (MDM), Intelligent Automation and Smart Factory initiatives. This role applies advanced knowledge acquired through relevant and substantial work experience. As the lead developer, this role is also comfortable experimenting with new techniques and coaching other development staff on AI-assisted and Agentic software delivery practices. This role assists others with more complex problems and designs elegant solutions to tackle them., * Design and implement agentic software architectures where AI agents perform code generation, test automation, and documentation, always under human oversight with deterministic guardrails and clear accountability boundaries. * Build agent workflows that exercise rules management, auditability, deterministic logic, high trust thresholds, and reusability across domains, using MDM and data quality platforms as foundational workloads, with fallback-to-human protocols for safety-critical decisions. * Design and implement advanced RAG architectures that ground AI responses in authoritative enterprise data. * Build and maintain vector stores, embedding pipelines, and hybrid retrieval strategies optimized for domain-specific technical content. * Enforce data classification, export control boundaries, and role-based access controls. * Develop event-driven integrations aligned to digital thread principles. * Build AI-enabled capabilities that consume digital thread events to automate downstream decision-making and exception detection. * Implement thread contracts to ensure deterministic, auditable system behavior that eliminates manual reconciliation. * Design and maintain AI-enabled applications using Python, C#/.NET on Microsoft Azure, leveraging Azure OpenAI, Claude, Azure AI Search, Databricks, and agent frameworks (Semantic Kernel, AutoGen, LangChain, or equivalent). * Implement CI/CD pipelines, Infrastructure as Code, automated testing, monitoring, telemetry, and operational runbooks for production-grade reliability. * Implement rule-level execution logs, record-level lineage, match/merge traceability, and interface health dashboards with explainability layers for state changes and agent decisions. * Ensure embedded governance-by-design and compliance with ITAR/EAR, CMMC/DFARS, and CUI handling requirements. * Collaborate with product owners, enterprise architects, data teams, and business stakeholders. * Coach and review the work of junior developers. ## Related Videos - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Agentic DevOps: How AI-Powered Automation Transforms Software Delivery on GitHub and Azure](https://www.wearedevelopers.com/videos/1539-agentic-devops-how-ai-powered-automation-transforms-software-delivery-on-github-and-azure) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)