AI Solution Architect

Role Overview:

We are seeking a highly experienced AI Solution Architect to design, develop, and integrate cutting-edge AI models and systems. The ideal candidate will bring deep expertise in AI algorithms, machine learning, and deep learning, combined with experience in deploying scalable AI systems in cloud and hybrid environments. Knowledge of EdTech-specific challenges and technologies is highly desirable.

Key Responsibilities:

• Lead the design and implementation of AI solutions, including developing custom algorithms for structured, unstructured, and multimodal data.
• Architect and deploy machine learning and AI models on cloud platforms using services such as AWS Bedrock, Google Vertex AI, and other cloud frameworks.
• Manage the AI model lifecycle, leveraging MLOps and LLMOps pipelines for efficient deployment, monitoring, and updates.
• Implement and optimize algorithms for:
• Image Processing: Classification, segmentation, object detection, and generative tasks.
• Text Processing: Natural language understanding, text summarization, translation, and sentiment analysis.
• Speech/Audio Processing: Speech recognition, audio classification, and signal analysis.
• Time Series and Anomaly Detection: Forecasting, anomaly detection, and real-time analytics.
• Design and fine-tune open-source LLMs and generative AI models for educational use cases.
• Establish governance frameworks for AI ethics, security, and compliance, particularly in the EdTech domain.
• Stay abreast of the latest advancements in AI technologies and apply them to solve complex business problems.
• Collaborate with cross-functional teams to integrate AI capabilities into new and existing products.
• Mentor and guide a team of AI engineers and data scientists, fostering technical growth and innovation.

Requirements:

• Experience:
• 11+ years in AI/ML, with at least 5 years in solution architecture roles.
• Proven track record of designing and deploying large-scale AI solutions in production environments.
• Technical Expertise:
• Mastery of AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face.
• Deep knowledge of algorithms for computer vision, natural language processing, and time series analysis.
• Experience with cloud AI services (AWS Bedrock, Google Vertex AI, Azure AI) and open-source LLM frameworks.
• Strong understanding of MLOps and LLMOps principles, including containerization, CI/CD pipelines, and Kubernetes orchestration.
• Proficiency in implementing explainable AI (XAI) techniques and responsible AI practices.
• Domain Knowledge:
• Familiarity with EdTech standards (LTI, xAPI, QTI) and technologies.
• Understanding of educational content creation, delivery systems, and adaptive learning models.
• Soft Skills:
• Excellent communication and leadership abilities to drive technical teams and engage stakeholders.
• Strategic mindset with strong problem-solving skills and a focus on business outcomes.
• Education:
• Bachelors or Masters degree in Computer Science, AI, Data Science, or related fields.
• Master in AI/ML is a plus.