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 settings 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

📌 Artificial Intelligence Architect Noida
🏢 Conduent
📍 Noida