GenAI Architect

About the Role

We are seeking an experienced and visionary AI Architect to lead Generative AI development services at QualiZeal. This individual will define the technical architecture, design principles, and governance models for all GenAI-related initiatives, including our flagship platform QMentisAI and enterprise-grade AI solutions for clients.

The ideal candidate will bring deep expertise in software architecture, AI/ML platforms, and enterprise integrations, combined with a strong understanding of RAG, MCP (Model Context Protocol), and agentic AI frameworks (LangChain, LangGraph, LlamaIndex, etc.). This role requires a strategic thinker who can balance innovation with scalability, performance, and compliance while mentoring teams and aligning solutions with business objectives.

Key responsibilities

• Design scalable, secure, and high-performance GenAI architectures and platforms.
• Build and implement LLM, RAG, AI agent, and cloud-native AI solutions.
• Define architecture standards, AI governance, and MLOps best practices.
• Lead technical evaluations and integrate GenAI frameworks such as LangChain, LangGraph, LlamaIndex, and MCP.
• Guide Agile development teams and oversee AI solution delivery.
• Integrate AI solutions with enterprise systems such as JIRA, Azure DevOps, SAP, GitHub, and Confluence.
• Mentor engineers and drive AI innovation, POCs, and client-focused AI initiatives.

Required skills

• 10+ years in software development and solution architecture.
• 3–5+ years of hands-on experience in AI/ML and Generative AI.
• Strong expertise in Python, .NET Core, or Java.
• Experience with LLMs, RAG pipelines, vector databases, embeddings, and AI search frameworks.
• Cloud expertise in Azure (preferred), AWS, or GCP.
• Knowledge of Docker, Kubernetes, CI/CD, MLOps, and API-first microservices.
• Strong stakeholder management, leadership, and communication skills.