Senior AI Solutions Architect

4 days ago


erode, India beBeeArtificial Full time

Unlock the Power of AI EngineeringWe are seeking an experienced Lead AI/ML Engineer to join our team and lead the development of cutting-edge artificial intelligence and machine learning solutions.About the RoleThe ideal candidate will have a strong background in architecting scalable ML pipelines, services, and platforms using modern cloud and MLOps practices. This includes designing and implementing robust model training, optimization, and evaluation workflows, as well as ensuring seamless integration with business applications.ResponsibilitiesDevelop and integrate Generative AI models (LLMs, Vision Models, Multimodal Models) into business applications, leveraging expertise in Python, ML frameworks (TensorFlow / PyTorch), and deep understanding of GenAI concepts.Work with agentic AI frameworks to design autonomous and semi-autonomous AI agents, showcasing hands-on experience with tools like LangChain, AutoGen, LlamaIndex, or similar.Collaborate with cross-functional stakeholders to translate business needs into AI-driven solutions, applying problem-solving abilities and converting challenges into innovative AI-based solutions.Lead code review and mentor junior engineers, ensuring best practices in model development and deployment, as well as guiding teams on emerging technologies and trends.Stay up-to-date with industry advancements by evaluating new tools, frameworks, and approaches to maintain the cutting-edge status of our AI ecosystem.Qualifications8–10 years of hands-on experience in Machine Learning, Deep Learning, and AI Engineering.Prior experience architecting AI/ML systems, including solution design, model lifecycle management, and scalability considerations.Required Skills and QualificationsExpertise in Python, ML frameworks (TensorFlow / PyTorch)Model training, optimization, and evaluationData engineering concepts & ML pipeline automationDeep understanding of GenAI, including LLMs, prompt engineering, fine-tuning, embeddings, vector DBs, and RAG.Hands-on experience with agentic AI frameworks (LangChain, AutoGen, LlamaIndex, or similar).Cloud experience (AWS, Azure, or GCP) with MLOps tools such as SageMaker, Vertex AI, MLflow, Kubeflow, etc.Strong problem-solving abilities with the ability to convert business challenges into AI-based solutions.



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