Description

You will design and implement end-to-end generative AI systems for enterprise use cases.

Responsibilities

• Design end-to-end generative AI architectures, including LLMs, diffusion models, and multimodal systems.
• Architect scalable pipelines for text, image, audio, and video generation using LangChain, Hugging Face, and custom models.
• Fine-tune and deploy models such as GPT-4, Llama, Claude, Stable Diffusion, and DALL-E.
• Optimize models for performance, cost, and ethical alignment, including bias mitigation and hallucination control.
• Define best practices for prompt engineering, RAG, and model evaluation while mentoring engineers and data scientists.
• Implement CI/CD pipelines for generative AI using MLFlow, Kubeflow, or Vertex AI.
• Integrate solutions with AWS Bedrock, Azure OpenAI, or GCP Vertex.
• Research agentic systems and autonomous AI while establishing governance frameworks for responsible AI.

Required Skills

• 5+ years of experience in relevant roles.
• Deep expertise in RAG architecture and NLP.
• Hands-on experience with MLOps tools including MLFlow and Kubeflow.
• Proficiency with TensorFlow.
• Cloud experience with AWS.
• Experience with LLMs (GPT-4, Llama, Claude) and diffusion models.
• Knowledge of LangChain and Hugging Face frameworks.
• Ability to implement CI/CD for generative AI workflows.

Key Skills

Education

Any Gradute