Job Title : AI Architect
Experience : 8 to 15 Yrs
Location : PAN India
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)