Artificial Intelligence Architect

Responsibilities:

• Lead hands-on design and development of analytics, AI, and GenAI platforms, solutions, and services.
• Establish reusable reference architectures, design patterns, standards, and architectural guardrails.
• Support design and governance of enterprise GenAI capabilities including RAG, Agentic AI, multi-agent

orchestration, prompt frameworks, knowledge management, and evaluation frameworks.

• Define Responsible AI, security, privacy, observability, model lifecycle management, and operational governance

controls.

• Lead architecture, design, and implementation decisions across cloud-native applications, APIs, integrations, data

platforms, containers, and DevOps pipelines.

• Champion AI architecture strategy across data, model, application, and cloud infrastructure layers, including

Generative AI, AI/ML platforms, model governance, responsible AI, security, observability, and scalable production

deployment patterns.

• Provide architecture leadership across multiple concurrent initiatives and work with delivery teams through

implementation and production deployment.

• Support solution sizing, proposals, client discussions, and technology modernization initiatives.
• Mentor engineers, technical leads, and architects while driving adoption of engineering best practices and

development standards.

• Design and implement products and platforms that comply with the standards and best practices across multiple

businesses & domains. Support architecture reviews & alignment with enterprise architecture and governance

standards.

• Drive the design, sizing, setup, and optimization of cloud environments and related services.
• Advise on emerging technology trends and recommend adoption opportunities to maintain competitive advantage.

Experience Needed:

• 15+ years of industry experience, including at least 5 years of experience as lead architect designing and building

cloud-native analytics and AI / GenAI solutions. Hands-on Azure experience is required.

• Hands-on experience delivering GenAI solutions into production environments including designing and governing

enterprise AI architectures, prompt and RAG (retrieval-augmented generation) patterns, responsible AI controls &

guardrails, AI orchestration, AI/ML model lifecycle management, and secure integration of AI capabilities into

analytics and enterprise applicationsRole & responsibilities

Preferred candidate profile