Senior AI Architect

Roles and Responsibilities

• Design and develop cutting-edge AI solutions using advanced analytics, machine learning, and deep learning techniques.
• Collaborate with cross-functional teams to integrate AI models into existing systems and applications.
• Develop data pipelines to extract insights from structured and unstructured data sources.
• Ensure scalability, reliability, and performance of deployed AI solutions.
• Provide technical guidance on best practices for implementing AI solutions.
• Define architecture across UI, APIs, microservices, AI services, databases, vector stores, integration and cloud infrastructure.
• Design secure enterprise AI solutions incorporating IAM, API security, encryption, data privacy, guardrails and responsible AI principles.
• Optimize AI solutions for latency, scalability, availability, token consumption and cloud cost.
• Lead architecture discussions, technical design reviews and solution workshops with customers and business stakeholders.

Job Profile

AI Architect with nearly 10 years of overall technology experience, specializing in architecting and delivering scalable AI, Generative AI, and cloud-native applications across any one of the leading hyperscalers including AWS, Microsoft Azure, and Google Cloud Platform (GCP). Experienced in designing enterprise-grade and public-facing AI applications with a strong focus on scalability, security, performance, reliability, and cost optimization.

Strong expertise in architecting LLM-based applications, RAG solutions, AI agents, conversational AI, document intelligence, predictive solutions, and AI-powered automation. Experienced in defining end-to-end architecture covering frontend applications, APIs, microservices, AI/ML services, vector databases, data platforms, integration layers, observability, security, and CI/CD.

Proven ability to translate business requirements into practical AI solutions, evaluate appropriate models and cloud services, lead technical teams, establish AI architecture standards, and take solutions from POC/MVP to production-scale deployment.