Ai Architect

Key Responsibilities:

Strategy & Roadmap

· 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

· 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

· 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

· Lead deployment of AI models using Docker, Kubernetes, and MLOps best practices.

· Integrate AI solutions with enterprise platforms and cloud-native services (Azure, AWS, GCP).

· Ensure performance, scalability, and security of deployed AI systems.

Leadership & Collaboration

· 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.

Must-Have Skills:

· Generative AI (Gen AI), Agentic AI

· AI Strategy, Architecture, and Roadmap Planning

· 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)

· AI Solution Assessment and Optimization