GCP-AI Architect

Job Description: You are seeking a visionary and hands-on AI Innovation Architect with a strong background in software engineering, cloud platforms, and Generative AI. You have 10+ years of experience in designing and delivering enterprise-grade solutions, with deep expertise in LLM integration, MCP protocol, RAG architecture, and AI-driven application design. Your role is pivotal in shaping the architecture and technical direction of AI-powered products and platforms, collaborating across engineering, product, and business teams to drive innovation and value. Key Responsibilities - Architect and lead the development of scalable, secure, and high-performance AI solutions using LLMs, RAG, and MCP. - Define and implement strategies for LLM model selection, prompt engineering, tool calling, and chunking optimization. - Collaborate with engineering teams to integrate AI capabilities into frontend (React, TypeScript) and backend (Python, FastAPI) systems. - Guide the implementation of OAuth 2.0, API-based system integrations, and cloud-native deployments (preferably on GCP). - Work closely with QA, DevOps, and delivery teams to ensure end-to-end solution quality and performance. - Engage with stakeholders to understand business needs and translate them into innovative AI architectures. - Provide technical leadership and mentorship across cross-functional teams. - Stay ahead of emerging AI trends and evaluate new tools, frameworks, and platforms for enterprise adoption. Qualifications - 10+ years of experience in software architecture and solution design. - Proven experience in: Generative AI, LLM integration, and RAG implementation. - MCP protocol, tool calling, and prompt engineering. - Python, FastAPI, and OAuth 2.0 for backend development. - React, TypeScript, and Tailwind CSS for frontend integration. - Strong understanding of cloud platforms, preferably Google Cloud Platform (GCP). - Experience in Agile delivery environments and stakeholder engagement. - Educational background: 10 + 2 + 4 (Bachelors degree in Computer Science, Engineering, or related field). Key Competencies - AI & System Architecture: Expertise in designing AI-first systems with scalable and modular architecture. - Innovation Leadership: Ability to drive innovation and influence technical direction across teams. - Stakeholder Management: Strong communication and expectation-setting skills with technical and business stakeholders. - Agile Execution: Experience leading Agile teams and delivering iterative value. - End-to-End Delivery: Proven ability to oversee architecture, development, and delivery processes.,