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)