Lead Full-stack Engineer - GenAI

About Blue Ridge Solutions, Inc

We are Blue Ridge, creators of the leading supply chain platform for distributors, retailers, and manufacturers. Our fast-growing and exciting SaaS supply chain planning platform provides cutting-edge supply chain solutions including forecasting and demand planning, replenishment, S&OP, rough-cut capacity planning, and pricing. Our software helps businesses gain control, improve forecasting precision, reduce costs, improve service levels, and increase profit.

We are looking for a passionate individual who is excited about the intersection of AI technology and supply chain optimization.  The Lead Full-stack Engineer - GenAI is responsible for building and deploying advanced machine learning systems with a focus on generative AI technologies that drive value for our supply chain solutions. You will lead the design and development of production-grade Generative AI (GenAI) and SaaS platforms. You’ll be the technical force behind scalable, secure, and intelligent systems that transform rapid PoCs into enterprise-ready solutions.

This is a strategic technical role within our AI/ML team, working at the intersection of cutting-edge research and practical implementation. You will be responsible for designing, developing, prototyping, improving and scaling ML systems from conception through production deployment, with emphasis on generative AI models and full-stack integration capabilities. 

Key Responsibilities 

GenAI/ML System Development 

•Design and develop Generative AI solutions using cloud-based managed AI services (e.g. Amazon Bedrock, Amazon SageMaker).

•Design and develop AI Agent workflows using cloud and open source agentic frameworks.

•Containerize AI applications and deploy them using cloud orchestration services.

•Collaborate with data architects/engineers to build end-to-end AI pipelines.

•Implement MLOps practices to automate the development, deployment, and monitoring of AI applications and models.

•Implement and manage robust monitoring systems for AI solutions in production environments, ensuring continuous performance tracking, anomaly detection, and model drift analysis; collaborate with cross-functional teams to deploy model updates, maintain version control, and optimize model efficiency over time.

•Use Infrastructure as Code (IaC) to manage and version cloud resources for AI projects.

•Ensure clear and accessible knowledge transfer to internal teams and create knowledge-sharing resources to ensure smooth transitions during model handoffs and system updates.

•Contribute to the development of best practices and standards for AI engineering within the organization.

Technical Leadership & Innovation 

• Lead the architecture and implementation of ML systems that can process supply chain data at scale 

• Research and implement cutting-edge ML techniques including transformer models, reinforcement learning, and generative adversarial networks 

• Optimize model performance for production environments, ensuring low latency and high availability 

• Establish best practices for model versioning, monitoring, and continuous integration/deployment 

Supply Chain Domain Excellence 

• Understand critical supply chain planning workflows and identify opportunities for AI-driven automation 

• Develop ML models that provide insights into potential supply disruptions and recommend automated resolutions 

• Build tools that increase the reach of supply chain solutions through partner integrations 

• Act as the voice of AI innovation within the supply chain domain 

Required Qualifications