AI ML Architect

Job description:

Mandatory Skills: Python, Machine Learning / Deep Learning Frameworks, Generative AI / Large Language Models (LLMs), Enterprise Architecture & Solution Design, AI/ML Platform Architecture, Cloud AI Services (Azure AI Foundry, Azure OpenAI)

Secondary Skills: Vector Databases, MLOps / LLMOps, Predictive Analytics, Performance Engineering, Splunk / Observability Tools, Docker, Kubernetes, CI/CD, Responsible AI Frameworks, Multi-Agent AI Systems

Seeking an experienced AI/ML Architect to define, architect, and lead the implementation of enterprise-scale AI/ML and Generative AI solutions across Quality Engineering, Performance Engineering, Automation, and Digital Transformation initiatives.

The ideal candidate will possess deep expertise in AI/ML architecture, GenAI platforms, cloud-native solution design, and enterprise integration patterns. This role requires strong technical leadership to drive AI strategy, establish architectural standards, and ensure scalable, secure, and responsible adoption of AI technologies across the organization.

Requirements

• Total 12+ years of overall IT experience in Enterprise Architecture, Platform Engineering, Quality Engineering, Performance Engineering, Data Engineering, or related technology domains.
• Minimum 5+ years of experience designing and delivering enterprise AI/ML solutions.
• Minimum 3+ years of experience architecting Generative AI, Agentic AI, or LLM-based platforms.
• Design and oversee the development of AI/ML solutions to meet strategic business objectives, ensuring alignment with the organization's data strategy and technological infrastructure.
• Evaluate and select appropriate AI/ML algorithms and models for specific business challenges, considering factors like accuracy, efficiency, and scalability.
• Architect scalable and secure AI/ML infrastructure, including data pipelines, storage, and computational resources, to support model training and deployment.
• Collaborate with data engineers, scientists, and business stakeholders to understand data requirements, availability, and quality for AI/ML projects.
• Establish best practices and governance for AI/ML, Generative AI, MLOps, and LLMOps, including model development, deployment, monitoring, Responsible AI, and lifecycle management.
• Lead the design and integration of Generative AI solutions, including AI Copilots, RAG-based systems, intelligent assistants, and multi-agent workflows using Azure AI Foundry, Azure OpenAI, and related AI platforms.
• Architect and optimize AI solutions to meet enterprise requirements for scalability, performance, security, reliability, observability, and seamless user experience.
• Monitor advancements in AI/ML, Generative AI, Agentic AI, and LLM technologies, incorporating innovative approaches to enhance business outcomes and solution capabilities.
• Advocate for AI literacy and enterprise-wide AI adoption by mentoring teams, conducting architecture reviews, and guiding stakeholders on AI/ML best practices and innovation opportunities.