AI Solutions Architect

Job Description

AI Solutions Architect

We are seeking an experienced AI Solutions Architect to join our team. The successful candidate will be responsible for designing and architecting artificial intelligence (AI) solutions to drive business innovation and digital transformation.

Responsibilities

• Collaborate with business stakeholders, data scientists, and engineering teams to understand requirements and translate them into AI solution architectures
• Design end-to-end AI solution architectures, including data pipelines, model training/deployment, and integration with existing systems
• Evaluate and recommend AI technologies, platforms, and tools that align with business objectives and technical requirements
• Develop reference architectures, best practices, and guidelines for building and deploying AI solutions at scale
• Provide technical leadership and mentorship to cross-functional teams throughout the AI solution delivery lifecycle
• Ensure AI solutions adhere to security, compliance, and governance standards
• Stay up-to-date with the latest AI trends, technologies, and industry best practices
• Evangelize and promote the adoption of AI solutions within the organization

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
• 5+ years of experience in designing and architecting enterprise-level software solutions
• Strong understanding of AI/ML concepts, algorithms, and techniques (e.g., supervised/unsupervised learning, deep learning, natural language processing)
• Proficiency in AI/ML frameworks and libraries (TensorFlow, PyTorch, scikit-learn, etc.)
• Experience with cloud computing platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes)
• Knowledge of data engineering, data pipelines, and data governance practices
• Familiarity with DevOps practices, including CI/CD, infrastructure as code, and monitoring
• Excellent problem-solving, analytical, and critical thinking skills
• Strong communication and collaboration abilities

Preferred Qualifications:

• Experience with specific AI use cases (e.g., computer vision, natural language processing, predictive analytics)
• Knowledge of big data technologies (Hadoop, Spark, etc.) and data lake architectures
• Familiarity with machine learning operations (MLOps) principles and practices
• Relevant industry certifications (e.g., AWS Certified Machine Learning Specialty, GCP Professional ML Engineer)

The AI Solutions Architect plays a crucial role in driving the successful adoption and implementation of AI solutions within the organization. The ideal candidate should have a strong technical background in AI/ML, coupled with excellent architectural design skills and the ability to collaborate effectively with cross-functional teams to deliver innovative and scalable AI solutions