Enterprise Architect AI

Description: We are seeking a seasoned AI Architect with 10+ years of experience in enterprise architecture, software engineering, and AI/ML solution design. This role demands a strategic thinker and technical leader who can drive AI innovation across the organization, architect scalable solutions, and mentor cross-functional teams. The ideal candidate will have a proven track record of delivering impactful AI systems in complex environments. Key Responsibilities: Strategic Leadership • Define and lead the enterprise-wide AI strategy and architecture roadmap. • Collaborate with executive leadership to align AI initiatives with business objectives. • Evaluate emerging AI technologies and guide adoption across business units. Architecture & Solution Design • Architect robust, scalable, and secure AI/ML platforms and solutions. • Lead the design of data pipelines, model training workflows, and deployment frameworks. • Integrate AI capabilities into existing enterprise systems using APIs and microservices. Governance & Risk Management • Establish AI governance frameworks including model lifecycle management, auditability, and ethical AI practices. • Ensure compliance with global data privacy regulations (GDPR, CCPA, etc.). Technical Leadership • Mentor and guide data scientists, ML engineers, and software developers. • Promote best practices in MLOps, DevOps, and cloud-native AI development. • Lead technical reviews, architecture boards, and innovation workshops. Performance & Optimization • Monitor AI systems in production and optimize for performance, scalability, and cost-efficiency. • Implement feedback loops and continuous learning systems for model improvement. Work Environment • Must work from either TCS Edison office or customer office for all 5 days Qualifications: • Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or related field. • 10+ years of experience in software architecture, with 5+ years focused on AI/ML. • Deep expertise in Python, TensorFlow, PyTorch, and cloud platforms (AWS, Azure, GCP). • Strong background in data engineering, distributed systems, and enterprise integration. • Experience with MLOps tools (MLflow, Kubeflow, Airflow) and containerization (Docker, Kubernetes). • Experience with generative AI, LLMs, and NLP. • Certifications in cloud architecture or AI/ML (e.g., AWS Certified Machine Learning, Azure AI Engineer). • Familiarity with industry-specific AI applications (e.g., manufacturing, healthcare, finance). • Excellent communication, leadership, and stakeholder management skills. #LI-MG2

Created: 2026-03-10