Principal .NET Software Engineer

Overview

As Principal AI Lead, you define the AI strategy and architecture for the Infor MES platform and Manufacturing portfolio, aligning AI investments with customer value and enterprise-grade security. You shape scalable, secure AI-enabled features and data models, collaborating with cross-functional teams to deliver practical manufacturing solutions. You influence technical direction, governance, and platform components, driving AI acceleration initiatives. This role blends hands-on engineering leadership with strategic roadmap work in a cloud-native SaaS context.

Responsibilities

• Define the AI architecture, standards, and technical strategy for MES and the Manufacturing portfolio
• Design scalable, secure AI-enabled product features using cloud-native and SaaS principles
• Build production AI feature sets, reference implementations, and reusable platform components
• Define API strategies and integration patterns for AI interactions with MES processes
• Lead data modelling, ontology strategy, semantic understanding, and business context for AI-driven experiences
• Provide architectural leadership across AI, Integration, IoT, Connected Worker, and platform teams
• Establish engineering standards for security, governance, observability, and responsible AI
• Evaluate emerging AI technologies, frameworks, and architectures
• Mentor engineers and act as a technical authority for AI initiatives
• Contribute to long-term technical strategy and roadmap planning for AI Acceleration initiatives

Key requirements

• Enterprise software/platform engineering experience
• Hands-on software development with modern practices
• Proven experience delivering production AI solutions with LLMs
• Experience with Retrieval Augmented Generation, agentic architectures, AI orchestration frameworks, and tool-based AI systems
• Experience integrating AI into enterprise software products
• API design, service contracts, and software architectures
• Cloud-native development and modern SaaS architectures
• Semantic modelling, ontologies, knowledge graphs, or domain-driven modelling for complex domains
• Strong software architecture knowledge including security, scalability, reliability, and observability
• Excellent C# and .NET experience and relational database knowledge
• Ability to influence technical direction across multiple teams
• Excellent communication and stakeholder management skills

• Strong communication
• Stakeholder management
• Mentoring and coaching
• LLMs and production AI
• Retrieval Augmented Generation (RAG)
• Agentic architectures and AI orchestration frameworks

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