What are the responsibilities and job description for the Principal AI Architect position at Generac?
The Principal AI Architect designs, develops and implements advanced AI solutions and architectures that align with the company’s strategic goals and objectives.
Major Responsibilities
Education
Major Responsibilities
- Leads the design and development of AI architectures, including machine learning models, deep learning frameworks, and generative AI systems
- Defines technical strategies and roadmaps for AI-driven projects ensuring alignment with business objectives
- Collaborates with data scientists, data engineers, business functional and product teams to integrate AI solutions into production environments
- Advises and oversees the evaluation and adoption of AI technologies, tools, and platforms
- Serves as the technical leader and mentor to AI and engineering teams
- Delivers scalable, secure, and optimized AI solutions
- Leads analytic literacy of the organization and serves as a translator of deep technical concepts into simple business vernacular
- Leads industry trends and advancements in AI to help maintain a competitive edge
- Communicates complex technical concepts to non-technical stakeholders effectively.
- Bachelors Degree in Computer Science or other related program
- 8 or more years of experience in AI, machine learning, or data science, with at least 4 years in a senior or lead architect role
- Proven track record of designing and deploying large-scale AI systems in production environments
- Experience leading cross-functional teams in the delivery of complex AI projects
- Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Must be deeply curious, desire to experiment
- Expertise in machine learning algorithms, Neural networks, Genetic Algorithms, Decision trees, Business dynamic models, Agent based models, Advanced statistical techniques and operations research
- Strong proficiency in programming languages such as Python, R, or Java
- Ability to design scalable, secure, and efficient AI architectures
- Exceptional problem-solving and analytical skills
- Strong leadership and mentorship abilities, with a focus on fostering innovation and collaboration
- Excellent communication skills, capable of translating technical concepts to diverse audiences
- Ability to work in a fast-paced, dynamic environment and manage multiple priorities
Education
- Ph.D. In Operations Research, Data Science, or a closely related field
- Master’s degree in a relevant field with significant research or project work in AI or machine learning
- Relevant certifications such as AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate
- Experience with generative AI and reinforcement learning
- Publications or patents in AI, machine learning, or related fields
- Familiarity with DevOps practices and MLOps pipelines for AI deployment
- Experience in industries such as healthcare, finance, or technology