Position Details: Enterprise Architect AI

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