AI Architect

Reports To: SVP

Job Overview:

We are seeking a highly skilled and visionary Senior Artificial Intelligence Architect to lead our cutting-edge AI initiatives and drive the development and implementation of advanced AI solutions. The ideal candidate will have extensive experience in AI and machine learning (ML), including expertise in Large Language Models (LLMs) and cloud-based AI services. They should possess a deep understanding of current AI technologies and trends, and a proven ability to lead and inspire a team of AI professionals.

Key Responsibilities:

1. Leadership and Strategy:
• Define and drive the AI strategy in alignment with the companys vision and goals.
• Head, Lead, mentor, and manage a team of AI engineers, data scientists, and researchers.
• Foster a culture of innovation, collaboration, and continuous learning within the AI team.
2. AI Solution Development:
• Oversee the design, development, and deployment of AI and ML models and solutions.
• Ensure the scalability, reliability, and performance of AI systems.
• Identify and implement best practices for AI and ML development and deployment.
3. Technical Expertise:
• Provide technical leadership and guidance in AI and ML technologies.
• Stay abreast of the latest advancements and trends in AI, ML, and related fields.
• Evaluate and recommend new tools, technologies, and frameworks to enhance AI capabilities.
4. Collaboration and Integration:
• Work closely with cross-functional teams, including product management, engineering, and data teams, to integrate AI solutions into products and services.
• Collaborate with stakeholders to understand business needs and translate them into AI solutions.
• Ensure seamless integration of AI systems with existing IT infrastructure.
5. Research and Innovation:
• Drive research initiatives to explore new AI technologies and applications.
• Encourage and support the team in publishing research papers and participating in industry conferences.
• Foster partnerships with academic and research institutions to advance AI knowledge and capabilities.
6. Project Management:
• Oversee multiple AI projects, ensuring they are delivered on time, within scope, and within budget.
• Monitor project progress, manage risks, and implement mitigation strategies.
• Provide regular updates to senior management on AI initiatives and project status.
7. LLM and Advanced AI Technologies:
• Lead the development and implementation of solutions leveraging Large Language Models and other advanced AI technologies.
• Oversee the fine-tuning and deployment of LLMs for various business applications.
• Explore and implement emerging AI technologies such as few-shot learning, transfer learning, and multi-modal AI systems.
8. Cloud-based AI Services:
• Design and implement AI solutions using cloud-based services, with a focus on Azure AI services.
• Optimize the use of cloud resources for AI workloads, ensuring cost-effectiveness and performance.
• Develop strategies for hybrid and multi-cloud AI deployments.

Qualifications:

• Bachelors degree in Computer Science, Data Science, AI, or a related field. A Masters or Ph.D. is highly preferred.
• 6+ years of experience in AI and ML, with at least 3 years of hands-on experience with Large Language Models and cloud-based AI services.
• Strong expertise in AI/ML frameworks, tools, and technologies (e.g., TensorFlow, PyTorch, Hugging Face Transformers, LangChain).
• Proven experience with Azure AI services, including Azure Machine Learning, Azure Cognitive Services, and Azure OpenAI Service.
• Experience with other cloud AI platforms (e.g., AWS SageMaker, Google Cloud AI) is a plus.
• Solid understanding of data structures, algorithms, software architecture, and MLOps practices.
• Experience with big data technologies and platforms (e.g., Hadoop, Spark).
• Excellent leadership, communication, and interpersonal skills.
• Proven ability to manage and mentor a team of AI professionals.
• Strong problem-solving and decision-making abilities.
• Ability to manage multiple projects simultaneously and prioritize effectively.

Preferred Skills:

• Experience with natural language processing (NLP), computer vision, or other specialized AI domains.
• Knowledge of cloud platforms and services (e.g., AWS, Azure, Google Cloud) related to AI and ML.
• Certification in AI/ML or related fields
• Experience with prompt engineering, few-shot learning, and fine-tuning of large language models.
• Familiarity with ethical AI practices, including bias mitigation and responsible AI development.
• Knowledge of AI-specific hardware acceleration (e.g., GPUs, TPUs) and optimization techniques.
• Experience with AI model compression techniques and edge AI deployment.
• Familiarity with AI governance frameworks and compliance standards.
• Experience with AI explainability and interpretability techniques.
• Knowledge of quantum computing and its potential applications in AI.

Key Technologies:

• Large Language Models (e.g., GPT, BERT, T5)
• Azure AI services (Azure Machine Learning, Azure Cognitive Services, Azure OpenAI Service)
• MLOps tools and practices
• Vector databases and semantic search technologies
• AI-specific hardware (GPUs, TPUs)
• Containerization and orchestration tools (Docker, Kubernetes)