Description

You will design and deliver production-grade Generative AI solutions on Google Cloud Platform.

Responsibilities

• Architect and deploy scalable GenAI systems using Gemini models, RAG pipelines, and agentic workflows.
• Build end-to-end MLOps pipelines for training, evaluation, and monitoring using Vertex AI, Kubeflow, and Terraform.
• Optimize LLM performance through fine-tuning, prompt engineering, and model compression techniques.
• Implement secure GCP infrastructure with strict IAM, VPC, and data privacy controls.
• Mentor engineers and define technical roadmaps for AI/ML initiatives.

Required Skills

• 5–8+ years of industry experience in Machine Learning.
• 3+ years of hands-on experience building and deploying Generative AI / LLM-based solutions in production.
• Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Deep experience with Google Cloud Platform (GCP), including Vertex AI, BigQuery, Dataflow, and Cloud Run.
• Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face.
• Solid understanding of SQL and unstructured data processing.
• Experience with Docker, Kubernetes (GKE), and CI/CD pipelines.

Preferred Skills

• Experience with multi-agent systems and orchestration (LangGraph, AutoGen).
• Deep understanding of vector databases (Vertex AI Vector Search, Pinecone, Chroma).

Key Skills

Education

Any Graduate