Lead AI Consultant / Senior AI Architect
About the role
We are looking for an experienced Lead AI Consultant / Senior AI Architect to lead the design and implementation of enterprise-scale AI solutions. This role will be responsible for defining AI architecture, providing technical direction, and ensuring successful delivery of AI initiatives involving LLM, RAG, Multi-Agent Systems, and Cloud technologies.
Key responsibilities
Design and define end-to-end architecture for enterprise AI and Generative AI solutions.
Lead the development and implementation of solutions using Large Language Models (LLM), Retrieval-Augmented Generation (RAG), and Multi-Agent Systems.
Design scalable, secure, and production-ready AI/ML architectures.
Provide technical leadership and architectural guidance to AI/ML engineering teams.
Evaluate and recommend appropriate AI models, frameworks, tools, and technologies based on business requirements.
Design and manage AI workloads and infrastructure on Google Cloud Platform (GCP).
Collaborate with business stakeholders, Product, Engineering, Data, and other technical teams to translate business requirements into AI solutions.
Establish best practices for AI development, deployment, integration, monitoring, security, and governance.
Conduct technical reviews and ensure the quality and performance of AI solutions.
Support troubleshooting, optimization, and continuous improvement of deployed AI solutions.
About you
Minimum Bachelor's Degree (S1) in Computer Science, Informatics Engineering, Information Technology, or related field.
Minimum 7 years of professional experience in AI/ML Engineering or related fields.
Proven experience as a Technical Lead, AI Architect, Lead AI Engineer, or similar role in enterprise AI projects.
Strong hands-on knowledge of Large Language Models (LLM) and Generative AI.
Strong understanding and implementation experience with Retrieval-Augmented Generation (RAG).
Experience designing or implementing Multi-Agent / Agentic AI systems.
Strong understanding of AI/ML architecture, model integration, APIs, data pipelines, and production deployment.
Experience with Google Cloud Platform (GCP) for AI/ML workloads and cloud architecture.
Strong understanding of scalable and secure enterprise system architecture.
Strong analytical, problem-solving, communication, and stakeholder management skills.