Artificial Intelligence Architect-Immediate joiner

Key Responsibilities

AI Use Case Definition & Business Value Realization

• Partner with business stakeholders to identify, evaluate, and prioritize AI/ML use cases across functions such as Operations, Customer Experience, Risk, Finance, HR, Supply Chain, and IT.
• Define measurable business outcomes, KPIs, and value propositions including productivity improvement, cost optimization, revenue growth, and enhanced customer experience.
• Drive technology-led use cases such as Intelligent Automation, AIOps, Predictive Maintenance, Anomaly Detection, Knowledge Assistants, and Developer Productivity solutions.
• Convert complex business challenges into AI-powered solution approaches and implementation roadmaps.

AI Architecture & Solution Design

• Design scalable end-to-end AI/ML reference architectures covering data ingestion, feature engineering, model development, deployment, monitoring, and retraining.
• Define architecture patterns for Machine Learning, Deep Learning, Generative AI, and Large Language Model (LLM) solutions.
• Architect real-time and batch inference systems across cloud, hybrid, and on-premise environments.
• Ensure solutions meet enterprise standards for scalability, security, reliability, governance, and cost efficiency.

AI Platform & Technology Strategy

• Develop AI/ML platform strategies leveraging cloud-native, open-source, and commercial technologies.
• Provide architectural leadership for MLOps and LLMOps implementation, model lifecycle management, and CI/CD integration.
• Evaluate emerging AI technologies and recommend build, buy, or partner approaches.
• Drive standardization and best practices for enterprise AI platforms.

Governance, Security & Responsible AI

• Embed Responsible AI principles, including fairness, explainability, transparency, and ethical AI usage.
• Ensure compliance with enterprise security, privacy, regulatory, and risk management requirements.
• Collaborate with governance, security, and compliance teams to establish AI control frameworks and guardrails.

Required Skills & Qualifications

• 12+ years of experience in Technology Architecture, Data Engineering, AI/ML, or Enterprise Solution Design.
• Strong expertise in AI/ML, Generative AI, LLMs, MLOps, and Cloud Architecture.
• Experience designing enterprise-scale AI solutions on Azure, AWS, or GCP.
• Hands-on knowledge of AI frameworks and platforms such as Python, TensorFlow, PyTorch, LangChain, Vector Databases, Azure AI Services, OpenAI, Databricks, MLflow, and Kubernetes.
• Strong understanding of data platforms, model lifecycle management, inference architecture, and AI governance.
• Excellent stakeholder management, consulting, and communication skills.