Gen AI Solution Architect - Azure at Weekday AI

Noida, Uttar Pradesh, India -

Full Time

Start Date

Immediate

Expiry Date

17 Aug, 26

Salary

0.0

Posted On

19 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Gen AI Solution Architecture, Microsoft Azure, Azure OpenAI Service, Large Language Models, Retrieval-Augmented Generation, Vector Databases, Prompt Engineering, Python, REST APIs, Docker, Kubernetes, Microservices, Azure Machine Learning, Cloud Architecture, AI Orchestration Frameworks, MLOps

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 10+ years Location: NOIDA, Chennai, Bangalore, Pune, Kolkata, Gurgaon JobType: full-time We are seeking an experienced and forward-thinking Gen AI Solution Architect – Azure to lead the design, development, and deployment of enterprise-grade Generative AI solutions on the Microsoft Azure ecosystem. The ideal candidate will possess deep expertise in AI/ML architecture, cloud-native application development, and large language model (LLM) integration, along with a strong understanding of scalable enterprise systems. As a key technology leader, you will work closely with business stakeholders, engineering teams, data scientists, and product leaders to build innovative AI-powered platforms and intelligent automation solutions. This role requires a combination of strategic thinking, hands-on architecture experience, and strong technical leadership to drive successful AI transformation initiatives. Key Responsibilities Design and architect scalable Generative AI solutions using Azure AI services and cloud-native technologies. Lead end-to-end solution architecture for AI/ML applications, including requirement gathering, system design, deployment strategy, and optimization. Develop enterprise AI frameworks leveraging Azure OpenAI Service, Cognitive Services, Azure Machine Learning, and related Azure offerings. Define architecture standards, best practices, security frameworks, and governance models for AI implementations. Collaborate with engineering and data teams to integrate LLMs, vector databases, RAG pipelines, prompt engineering strategies, and AI orchestration frameworks. Drive solution scalability, reliability, performance optimization, and cost efficiency across cloud environments. Work with cross-functional teams to translate business requirements into technical AI solutions. Provide technical leadership, mentorship, and architectural guidance to development teams. Evaluate emerging AI technologies, tools, and frameworks to enhance enterprise AI capabilities. Ensure compliance with enterprise security, privacy, and responsible AI standards. Must-Have Skills Strong experience as a Gen AI Solution Architect with expertise in designing enterprise AI platforms. Deep knowledge of Microsoft Azure cloud services and Azure-based AI ecosystem. Hands-on experience with Azure OpenAI Service, Azure AI Studio, Azure Machine Learning, Cognitive Services, and AI orchestration frameworks. Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector search, prompt engineering, and AI agents. Expertise in cloud architecture, microservices, APIs, distributed systems, and scalable application design. Experience with Python, REST APIs, and AI/ML deployment pipelines. Knowledge of containerization and orchestration technologies such as Docker and Kubernetes. Familiarity with data engineering concepts, vector databases, and enterprise integration patterns. Strong understanding of security, governance, compliance, and responsible AI practices. Excellent stakeholder management, communication, and problem-solving skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or related field. Azure certifications such as Azure Solutions Architect Expert or Azure AI Engineer Associate will be preferred. Experience working in enterprise digital transformation or AI modernization initiatives. Exposure to multi-cloud environments and MLOps practices is an added advantage. Experience 10 – 15 years of overall experience in software engineering, cloud architecture, or enterprise technology solutions. Proven experience in architecting and delivering large-scale AI/ML or Generative AI solutions in enterprise environments.

Responsibilities

Lead the design and deployment of enterprise-grade Generative AI solutions using the Microsoft Azure ecosystem. Collaborate with stakeholders to build scalable AI-powered platforms and define governance and security frameworks.