AI Architect

at  McCarthy Building Co

POSITION SUMMARY:

The AI Architect will oversee the design, development, and implementation of enterprise AI solutions, ensuring they meet business goals and technical requirements. This position will provide guidance for the strategic vision, technical direction, and overall alignment with organizational objectives. The AI Architect leads multidisciplinary teams to deliver high-value enterprise AI solutions, while promoting collaboration, technical excellence, and continuous innovation in AI capabilities.

SKILLS & QUALIFICATIONS:

• Bachelor’s or Master’s Degree in Computer Science, Data Science, or AI is preferred.
• 5+ years of proven experience architecting enterprise environments with 3+ years designing and deploying AI/ML/NLP/Deep Learning solutions.
• Strong expertise in building and evaluating LLM’s from at least one of the major vendors – Microsoft, Google, Amazon, OpenAI, and Anthropic.
• Proficiency in working with pre-trained AI models (e.g., ChatGPT, Llama), advanced NLP algorithms, and multi-modal or foundation models.
• Hands-on experience with tools and frameworks such as SQL, Python, PyTorch, TensorFlow, Kubernetes, Docker, and MLOps best-practices.
• Excellent collaboration skills, with the ability to design and implement AI solutions that align with business goals and engage cross-functional teams effectively.
• Proficiency in data engineering principles and best practices.
  McCarthy Building Companies is proud to be an equal opportunity and affirmative action employer regardless of race, color, gender, age, sexual orientation, gender identity, gender expression, religious beliefs, marital status, genetic information, national origin, disability, protected veteran status, or any other basis protected by federal, state, or local law

• Design, implement, and scale AI solutions for the enterprise.
• Identify, evaluate and ensure alignment of AI use cases with business strategies.
• Lead the evaluation and application of Large Language Models (LLMs) and Generative AI.
• Develop framework and processes for training, testing, deploying, and scaling AI models.
• Partner with IT teams to successfully integrate AI solutions into production systems.
• Proactively monitor LLMs for potential biases, inaccuracies, and hallucinations.
• Design data pipelines to support large language model training and inference.
• Support decision-making between using pre-built or custom developed AI solutions.
• Analyze data to fine-tune and optimize AI models.
• Communicate AI project results and insights to business stakeholders and teams.