Generative AI Architect

Experience Required: 8-10 Years

Job Summary

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.

Key Responsibilities

• 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 LangChain.

• 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 Google Cloud Platform).

• 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.

Required Technical Skills

• 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 LangChain 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, Google Cloud Platform).

• Deep understanding of Responsible AI principles and implementation.

Preferred Qualifications

• 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.