AI Architect

Job Summary We are seeking an experienced and innovative AI Architect to design, develop, and implement enterprise-level AI solutions that drive business transformation. The AI Architect will provide technical leadership in machine learning (ML), deep learning (DL), natural language processing (NLP), and generative AI, ensuring scalability, security, and integration with existing enterprise systems. This role requires strong collaboration with data scientists, engineers, and business stakeholders to translate business challenges into cutting-edge AI architectures. Key Responsibilities • Define and design the overall AI/ML architecture, ensuring scalability, performance, and cost efficiency. • Collaborate with business leaders, product teams, and data scientists to align AI strategies with organizational goals. • Evaluate, select, and integrate AI frameworks, platforms, and cloud services (e.g., AWS, Azure, GCP). • Lead the development of end-to-end AI solutions, including data ingestion, model training, deployment, monitoring, and governance. • Architect and guide the implementation of LLM-based solutions, generative AI, and intelligent agents. • Establish best practices for AI governance, ethics, fairness, explainability, and regulatory compliance. • Oversee MLOps pipelines for model lifecycle management, continuous integration, and deployment (CI/CD). • Ensure system security, data privacy, and compliance with relevant industry standards. • Mentor engineers and data scientists on advanced AI techniques and architecture patterns. • Stay current with emerging AI technologies and assess their potential impact on business operations. Required Skills & Qualifications • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field. • 8+ years of experience in software engineering, data engineering, or AI/ML solution development. • Proven experience as an AI Architect, ML Engineer, or AI Solutions Lead. • Expertise in ML, DL, NLP, Generative AI, and Large Language Models (LLMs). • Strong proficiency in Python, Java, or Scala, with experience in ML/DL frameworks (TensorFlow, PyTorch, Keras). • Hands-on experience with cloud AI/ML services (AWS SageMaker, Azure AI, GCP Vertex AI). • Knowledge of MLOps practices, CI/CD, and container orchestration tools (Docker, Kubernetes). • Solid understanding of data architecture, APIs, and system integrations. • Experience in building secure and ethical AI systems with transparency and explainability