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
- 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
- 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