Principal AI Engineer

Our client is a growing ERP software and technology services company that is expanding its AI product portfolio. The organization has a well-established core software business and is investing heavily in AI-powered products, automation, and internal engineering capabilities.

They are looking for a Principal AI Engineer to own the technical direction of AI products across the organization. This is a senior individual contributor position with significant influence over architecture, AI integration, engineering standards, and technology decisions.

You will work closely with executive and product leadership to determine what is technically feasible, design how solutions should be built, and provide architectural direction to the development team responsible for implementation.

This is a hands-on role for someone who enjoys solving complex technical problems, making architectural decisions, and influencing engineering teams without relying on direct authority.

What You’ll Work On

• Lead the technical architecture and AI integration strategy across a growing portfolio of AI-powered products and internal tools
• Design and implement AI solutions using modern foundation models, retrieval technologies, cloud services, and supporting infrastructure
• Help evolve AI-powered products serving highly regulated and compliance-focused industries
• Define how AI systems should be evaluated, monitored, and improved, particularly in applications where accuracy, traceability, and reliability are critical
• Establish technical standards for AI-assisted software development, including appropriate review processes, testing, and quality controls
• Evaluate emerging AI technologies and determine where they can provide meaningful business or product value
• Partner with product and innovation leadership to assess technical feasibility, architecture, timelines, and tradeoffs
• Provide architectural guidance to development teams throughout the product lifecycle
• Review and improve existing AI-enabled applications and codebases, including systems that were developed quickly and require additional architectural maturity
• Help establish scalable patterns for AI integration that can be reused across multiple products
• Participate in customer and partner technical discussions when architectural expertise is needed
• Help shape how AI can improve internal development, support, delivery, and operational workflows
• Document architectural decisions, technical standards, and system designs so knowledge can be shared across the engineering organization
• Maintain a strong focus on knowledge transfer and ensuring solutions can be effectively operated and maintained by the broader development team

What We’re Looking For

Required Qualifications

• Deep, hands-on experience designing and integrating production AI systems
• Proven experience architecting and shipping applications built with modern AI/ML models
• Strong understanding of AI architecture, model integration, retrieval, evaluation, and production deployment
• Ability to clearly explain technical tradeoffs, including decisions that did not work as expected
• Experience influencing and guiding engineers without having direct management authority
• Ability to establish, communicate, and defend engineering standards based on technical reasoning
• Strong documentation and design-review skills, with the ability to make architectural decisions understandable and reviewable by others
• Experience taking ownership of an existing codebase or system that you did not originally build
• Strong product mindset and ability to think beyond individual features or development sprints
• Comfortable working directly with senior leadership, product stakeholders, customers, and technical partners
• Strong communication skills and the ability to translate complex AI architecture decisions into practical recommendations

Technical Environment

The organization’s AI products currently operate primarily within AWS , with a strong emphasis on security, isolation, and production reliability.

The current environment includes:

Application

• C# / .NET
• Blazor WebAssembly
• REST APIs

AWS / Cloud Infrastructure

• AWS GovCloud
• AWS CDK, primarily using C#
• ECS Fargate
• AWS Lambda
• Amazon SQS
• Amazon EventBridge

Data

• Amazon RDS for SQL Server
• Amazon S3
• Multi-AZ database environments
• Object Lock

AI / Retrieval

• Amazon Bedrock
• Bedrock Knowledge Bases
• Embeddings and hosted …