Artizent - Lead AI/ML Engineer - AWS Platform

Job Summary : We are looking for an experienced Lead AI/ML Engineer to design and build scalable AI/ML solutions using AWS SageMaker, Amazon Bedrock, RAG architectures, and AI agents. The ideal candidate should have strong hands-on experience in designing data foundations for AI workloads, integrating foundation models, and fine-tuning AI/ML solutions for enterprise use cases. Key Responsibilities : - Design and develop robust data foundations to support AI/ML workloads using Amazon SageMaker and Amazon Bedrock. - Architect and implement Retrieval-Augmented Generation (RAG) solutions for enterprise AI applications. - Design scalable and production-ready AI/ML pipelines and infrastructure on AWS. - Work with Amazon Bedrock foundation models and implement effective model integration strategies. - Develop and integrate AI agents using Agent Core and related agentic AI capabilities. - Implement and optimize Claude-based AI solutions, ensuring effective model integration and performance. - Identify suitable AI/ML workloads and use cases based on business requirements and technical feasibility. - Fine-tune and optimize AI/ML models to improve accuracy, performance, latency, and cost efficiency. - Evaluate different foundation models and AI/ML approaches and recommend the most appropriate solutions. - Develop scalable architectures for LLM, Generative AI, and agentic AI applications. - Work closely with data engineering, software engineering, cloud, and business teams to translate requirements into AI/ML solutions. - Establish best practices around model evaluation, prompt engineering, RAG performance, security, governance, and responsible AI. - Monitor AI/ML solutions in production and continuously identify opportunities for optimization and improvement. - Provide technical leadership, conduct architecture reviews, and mentor team members on AI/ML and Generative AI technologies. Required Skills & Experience : - Strong experience in AI/ML engineering and solution architecture. - Hands-on experience with AWS SageMaker and Amazon Bedrock. - Strong understanding of Generative AI, Large Language Models (LLMs), and RAG architectures. - Experience working with Agent Core / agentic AI frameworks. - Strong experience integrating and working with Claude models. - Experience with AI/ML model fine-tuning, optimization, and evaluation. - Strong understanding of data pipelines and data foundations required for AI/ML workloads. - Experience designing scalable and production-ready AWS-based AI/ML architectures. - Strong programming skills in Python. - Experience with vector databases, embeddings, semantic search, and knowledge retrieval is highly desirable. - Understanding of MLOps/LLMOps, model monitoring, deployment, and lifecycle management. - Strong knowledge of cloud security, data privacy, and governance principles for AI/ML workloads. Leadership & Soft Skills : - Strong technical leadership and architecture capabilities. - Ability to evaluate emerging AI technologies and translate them into practical business solutions. - Excellent problem-solving and analytical skills. - Strong communication and stakeholder-management abilities. - Ability to mentor engineers and drive engineering best practices. Key Technologies : - AWS : SageMaker, Amazon Bedrock - GenAI : LLMs, RAG, Agentic AI, Claude - AI/ML : Model Fine-Tuning, Model Evaluation, MLOps/LLMOps - Programming : Python - Architecture : AI/ML Data Foundations, RAG Architecture, AI Agents