Agentic AI Architect

Job Requirements
· 10+ years of experience
. 5+ years in AI/Gen AI
. Proven experience in architecting and deploying AI/Gen AI systems in production environments
. Ability to design scalable, robust, and secure solutions with a focus on Gen AI,
. Comprehensive knowledge about Gen AI platforms and architecting integrated solutions
. Large Language Models (LLMs), and other advanced AI technologies
. Understanding of microservices, APIs and integration with existing systems
. Expertise in designing Gen AI solutions for enterprise use cases
. Proficiency in Python or R, along with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn)
. Experience with cloud-based AI services (e.g., AWS, Azure, GCP) for building scalable AI solutions
. Solid understanding of software development lifecycle (SDLC) and DevOps practices.
. Experience of LangChain, Phoenix, MLFlow, LangGraph, Google Agent Development Kit
. Experience of designing AI solutions using Agentic AI approach, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Vector Databases, etc.
. Comprehensive knowledge to assess and evaluate Agentic AI and Generative AI applications
· Excellent problem-solving skills and the ability to tackle complex business challenges using AI technologies.>
Key Responsibilities
Design and Implement AI Architecture
- Strategic Planning and Business Alignment
- Governance, Security, and Responsible AI
- Model Lifecycle Management and Optimization
- Collaboration and Integration >
Certifications
AWS Certified Machine Learning – Specialty
AWS Certified Solutions Architect – Associate
Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure AI Fundamentals
Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Cloud Architect
Google Cloud Certified: Generative AI Leader
Google Cloud Certified: Professional Machine Learning Engineer
Microsoft Certified: AI Agent Builder Associate

Work arrangement
No