Senior Gen AI Applications Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Develop and design scalable AI/ML solutions, including generative AI and agentic AI applications, aimed at grid automation, digital transformation, product-line applications, and enhancing business efficiency.

• Set architectural standards, best practices, and technical protocols for AI/ML development within the CTO organization.

• Establish technical foundations utilizing modular and microservices architectures, cloud and edge computing patterns, API-first and privacy-by-design methodologies, containerization, orchestration, autoscaling, infrastructure as code, CI/CD, data and MLOps pipelines, and collaborative experimentation settings.

• Create and implement solutions on GE GridNode and other edge platforms following container and microservices principles.

• Formulate strategies to enhance model performance in production environments.

• Provide guidance to project and product teams regarding architecture and solution strategies for generative AI and agentic AI applications.

• Develop and enforce monitoring, observability, and safety measures for generative AI and agentic AI solutions.

• Assist teams in creating production-grade systems and reusable frameworks that are scalable, dependable, and maintainable.

• Work alongside cross-functional teams to embed AI/ML capabilities into current platforms and to innovate new intelligent products and business-efficiency solutions.

• Keep abreast of advancements in AI/ML, generative AI, agentic AI, and energy-system technologies, translating these developments into actionable recommendations.

• Assess AI/ML tools, platforms, methodologies, and vendor solutions to address grid-automation challenges and exploit business opportunities.

• Design and implement proofs of concept to verify feasibility and guide production decisions.

• Report directly to the Director of Data Analytics and AI Solutions within the Grid Automation CTO organization.

⛳️ Requirements

• A Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a related technical discipline.

• At least 7 years of practical experience in software engineering, AI/ML development, and/or solution architecture.

• Proven hands-on experience in building and architecting generative AI and agentic AI solutions and applications.

• Experience in architecting and implementing generative AI and agentic AI solutions on AWS or similar cloud infrastructures, such as Microsoft Azure or Google Cloud Platform.

• Demonstrated expertise with machine learning frameworks, including TensorFlow, PyTorch, or scikit-learn.

• Familiarity with generative AI technologies, including large and small language models, diffusion models, and GANs.

• Experience with agentic AI frameworks and architectures, including multi-agent orchestration, tool and function calling, retrieval-augmented generation, agent memory, and planning.

• Experience in implementing monitoring, observability, and safety measures for generative AI and agentic AI systems.

• Practical experience applying AI/ML frameworks, AI/MLOps, and CI/CD in both cloud-native and on-premises development and deployment within operational technology or industrial automation environments.

• Experience in developing and deploying ML models using cloud MLOps services such as Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Dataiku Cloud, or equivalent platforms.

• Hands-on experience in developing and testing AI/ML algorithms, and familiarity with grid or physics models using tools like MATLAB, PSCAD, PSS/E, DIgSILENT PowerFactory, or equivalent software.

• Knowledge of DevOps, data pipelines, model registries, Docker, and Kubernetes.

• Experience in designing solutions throughout the entire AI/ML lifecycle.

• Strong foundation in edge computing, industrial IoT, real-time processing, and familiarity with AWS, Microsoft Azure, or Google Cloud Platform.

• Knowledge of graph databases, SQL and NoSQL databases, and Microsoft Access.

• Proficiency in Python and at least one other programming language, such as C# or C++.

• Experience with scientific programming or simulation tools like MATLAB or R.

• Knowledge of time-series analysis, signal processing, load forecasting, or predictive modeling relevant to energy systems and grid operations.

• Demonstrated success in delivering complex AI/ML projects from initial concept through to production deployment.

• Ability to translate research insights into practical business solutions and commercial applications.

• Understanding of industrial IoT, edge computing requirements, and real-time data processing in critical infrastructure settings.

🏝️ Benefits

• Discretionary annual bonus.

• Relocation Assistance Provided: No.