Applied AI Architect

About This Role

This role involves leading the design and implementation of enterprise-scale AI, ML, and Generative AI solutions. The architect will define vision, drive innovation, and guide end-to-end delivery of intelligent systems to enhance the platform and customer experience.

Responsibilities

• Design and lead the development of scalable AI/ML/GenAI-enabled product enhancements.
• Collaborate with Product, Engineering, Data, and DevOps teams to integrate AI into existing platform capabilities.
• Define the vision, roadmap, and governance for AI initiatives including platform selection, tooling, and best practices.
• Stay updated on emerging AI/ML and GenAI trends, conduct technical assessments, feasibility studies, and POCs.
• Establish and scale MLOps pipelines for experimentation, model training, deployment, and monitoring.
• Partner with data engineering and cloud teams to build robust data pipelines and infrastructure for AI workloads.
• Champion ethical AI practices by embedding fairness, transparency, explainability, and compliance.
• Guide and mentor technical teams on AI architecture, model operationalization, and real-world scalability.

Requirements

• 10+ years of experience in technology roles
• 3+ years focused on AI/ML architecture or enterprise-scale system design
• Deep understanding of machine learning, deep learning, and generative AI technologies and frameworks (e.g., TensorFlow, PyTorch, Hugging Face, LangChain)
• Strong knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI)
• Strong proficiency with cloud platforms (Azure preferred, AWS or GCP)
• Excellent communication and leadership skills

Qualifications

• Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, Engineering, or a related field; PhD preferred.
• 10+ years of experience in technology roles, with at least 3 years focused on AI/ML architecture or enterprise-scale system design. Demonstrated success in architecting and deploying production-ready AI/ML solutions at scale within complex, data-rich enterprise SaaS products.

Nice to Have

• Familiarity with retrieval-augmented generation (RAG), vector databases, fine-tuning of pre-trained models, and building voice or AI agents (e.g. MCP protocol)

Skills

* Required skills

Benefits