About the Role

Architect scalable ML pipelines, services, and platforms using modern cloud and MLOps practices.

Responsibilities

Build, fine-tune, and integrate Generative AI models (LLMs, Vision Models, Multimodal Models) into business applications.
Work with agentic AI frameworks to design autonomous and semi-autonomous AI agents.
Collaborate with cross-functional stakeholders to translate business needs into AI-driven solutions.
Review code, guide junior engineers, and ensure best practices in model development and deployment.
Evaluate new tools, frameworks, and approaches to keep the AI ecosystem cutting-edge.

Qualifications

810 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

Strong expertise in: Python, ML frameworks (TensorFlow / PyTorch)
Model training, optimization, and evaluation
Data engineering concepts & ML pipeline automation
Deep 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.

Gen-AI Architect