Generative AI Architect

Generative AI Architect

We are seeking a highly experienced Generative AI Architect to lead the design, architecture, and enterprise-wide adoption of AI-driven solutions. The ideal candidate will define the strategic vision for AI programs, establish architectural standards, and drive innovation using cutting-edge Generative AI technologies, including Large Language Models (LLMs), agentic frameworks, and vector databases.

This role requires deep technical expertise in AI architecture, strong Python programming skills, hands-on experience building intelligent agents using modern frameworks, and a strong understanding of Responsible AI practices.

• Define and design end-to-end enterprise AI solution architectures.
• Establish AI strategy, governance standards, and architectural guidelines.
• Lead the implementation of Large Language Model (LLM)-based systems and GenAI-powered applications.
• Design and implement AI agents using frameworks such as Lang Chain.
• Develop and integrate Model Context Protocol (MCP) components and custom tools within agent architectures.
• Architect and deploy solutions leveraging vector databases for embedding storage and semantic search.
• Design scalable AI solutions deployed in cloud environments (Azure, AWS, or GCP).
• Implement Responsible AI strategies, ensuring ethical, compliant, and explainable AI solutions.
• Collaborate with engineering, product, and data teams to translate business problems into AI-driven solutions.
• Mentor teams and drive AI innovation initiatives across the organization.

• 8–10 years of experience in AI/ML architecture and enterprise solution design.
• Strong expertise in Generative AI technologies and LLM frameworks.
• Hands-on experience building AI agents using Lang Chain or similar frameworks.
• Experience programming and customizing AI agents with external tools and MCPs.
• Strong proficiency in Python programming.
• Experience with vector databases (e.g., Pinecone, Weaviate, or similar).
• Experience deploying AI solutions in cloud environments (AWS, Azure, GCP).
• Deep understanding of Responsible AI principles and implementation.

• Experience designing AI Centers of Excellence (CoE).
• Exposure to MLOps, CI/CD pipelines for AI models.
• Experience with prompt engineering and fine-tuning LLMs.
• Strong communication and leadership skills.
• Demonstrated innovation mindset and ability to experiment with emerging AI technologies.