GenAI Solution Architect at Weekday AI

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

02 Aug, 26

Salary

2800000.0

Posted On

04 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GenAI Solution Architecture, Large Language Models, Prompt Engineering, Microservices Architecture, Distributed Systems, CI/CD Pipelines, DevOps, Python, Machine Learning, MLOps, Cloud Platforms, Vector Databases, Embeddings, Retrieval-Augmented Generation, System Design, Enterprise Applications

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 1800000 - Rs 2800000 (ie INR 18 - 28 LPA) Min Experience: 10 years Location: Telangana, Hyderabad JobType: full-time We are seeking an experienced and forward-thinking GenAI Solution Architect to lead the design and delivery of cutting-edge Generative AI solutions. This role requires deep expertise in end-to-end solution architecture, strong technical proficiency, and the ability to translate complex business requirements into scalable, secure, and high-performance AI-driven systems. You will play a critical role in shaping AI strategy, driving innovation, and enabling enterprise-wide adoption of GenAI technologies. Key Responsibilities: Design and architect end-to-end Generative AI solutions, ensuring alignment with business goals, scalability requirements, and technology standards. Lead solution design across multiple domains, integrating Large Language Models (LLMs), machine learning pipelines, and enterprise systems. Define architecture frameworks, best practices, and reusable components for GenAI implementations. Collaborate with cross-functional teams including data scientists, engineers, product managers, and stakeholders to deliver robust AI solutions. Evaluate and select appropriate tools, platforms, and models for GenAI use cases, balancing performance, cost, and maintainability. Drive implementation of CI/CD pipelines for ML and GenAI workflows, ensuring continuous integration, deployment, and monitoring. Provide technical leadership in building secure, compliant, and ethical AI systems. Guide teams in model fine-tuning, prompt engineering, and optimization of LLM-based applications. Conduct architecture reviews, risk assessments, and performance tuning for deployed solutions. Stay updated with the latest advancements in Generative AI, machine learning, and cloud-native architectures. Must-Have Skills: Strong expertise in GenAI solution architecture (end-to-end) including design, deployment, and scaling. Proven experience as a Solution Architect with a focus on complex system design and enterprise-grade applications. Deep understanding of solution design principles, microservices architecture, and distributed systems. Hands-on experience with Large Language Models (LLMs), prompt engineering, and GenAI frameworks. Solid knowledge of CI/CD pipelines for ML/AI systems and DevOps best practices. Good-to-Have Skills: Proficiency in Python for AI/ML development and automation. Strong foundation in Machine Learning concepts, model lifecycle management, and MLOps. Experience with cloud platforms (AWS, Azure, or GCP) and AI services. Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG). Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 10–15 years of overall experience, with significant exposure to AI/ML and architecture roles. Key Competencies: Strong analytical and problem-solving skills with the ability to design innovative solutions. Excellent communication and stakeholder management abilities. Ability to lead teams, mentor engineers, and drive technical excellence. Strategic mindset with a focus on delivering business impact through AI.

Responsibilities

Lead the design and delivery of scalable, secure, and high-performance Generative AI solutions aligned with business goals. Collaborate with cross-functional teams to integrate LLMs and machine learning pipelines into enterprise systems.