AI Architect

About the Company
AI/GEN AI Architect
About the Role
Experience Required: 8 to 15 Years
Role Overview: We are seeking a visionary AI Architect with 8–15 years of experience to lead the strategic design and implementation of enterprise-scale AI solutions. This role requires deep expertise in Generative AI, Agentic AI, and Responsible AI, along with a strong foundation in AI architecture, solution assessment, and cloud-native AI platforms. The AI Architect will define the roadmap, assess existing systems, and guide cross-functional teams in building scalable, secure, and ethical AI systems.
Key Responsibilities:
🔷 Strategy & Roadmap (Optional)
Define and drive the AI strategy, aligning with business goals and innovation priorities.
Develop and maintain the AI solution roadmap, including short-term deliverables and long-term vision.
Evaluate emerging AI trends and technologies to inform strategic direction.
🔷 Architecture & Design (Mandatory)
Architect end-to-end AI solutions using Gen AI, Agentic AI, LLMs, and multi-modal AI.
Design intelligent agent systems using LangChain, LangGraph, Model Context Protocol (MCP), and Agent to Agent Protocols.
Establish scalable and modular AI architectures that support RAG pipelines, Vector DBs, and Embeddings.
Define and enforce AI governance frameworks, including Responsible AI, GuardRails, and compliance with AI Ethics & Regulations.
🔷 Assessment & Optimization (Good to have)
Conduct technical assessments of existing AI/ML systems, models, and data pipelines.
Identify gaps, risks, and opportunities for modernization or enhancement.
Recommend architectural improvements and integration strategies for legacy systems.
🔷 Deployment & Integration (Mandatory)
Lead deployment of AI models using Docker, Kubernetes, and MLOps best practices.
Integrate AI solutions with enterprise platforms and ANY ONE cloud-native services (Azure, AWS, GCP).
Ensure performance, scalability, and security of deployed AI systems.
🔷 Leadership & Collaboration (Good to have)
Collaborate with product owners, data scientists, engineers, and business stakeholders.
Mentor engineering teams and contribute to talent development in AI and ML domains.
Represent AI architecture in enterprise governance forums and technical councils.
Technical Skills:
Generative AI (Gen AI), Agentic AI
Python Programming
AI Frameworks (LangChain, AutoGen, CrewAI and LangGraph)
Model Context Protocol (MCP), Agent to Agent Protocol
GuardRails, AI Ethics and Regulations
Prompt Engineering, Responsible AI
Distillation, RAG, Fine-tuning
Multi-modal AI, LLMs
Vector Databases, Embeddings
GenAI deployment tools (Docker, Kubernetes)

Work arrangement
No