Experience:

• 7 Years

Responsibilities:

• Design, train, fine-tune, and deploy scalable machine learning models and Generative AI solutions using Vertex AI and GCP
• Build and manage end-to-end deployment pipelines with Vertex AI pipelines, Model Registry, and Endpoints for real-time and batch inference
• Integrate commercial and open-source LLM APIs into enterprise applications
• Design and develop agentic AI workflows using orchestration frameworks such as LangChain and LlamaIndex
• Develop and optimize prompt engineering strategies using tools like Google ADK
• Implement and manage Model Context Protocol (MCP) integrations
• Leverage transformer architectures and build Retrieval-Augmented Generation (RAG) pipelines using vector databases and embeddings
• Architect and maintain automated data pipelines for continuous model training, evaluation, and inference
• Design highly available, scalable, and secure cloud-native architectures for AI workloads
• Implement MLOps best practices including CI/CD, model monitoring, and performance tuning in production
• Manage AI security, data privacy, and governance compliance within cloud environments

Additional responsibilities:

• Development experience with AI Guardrails

More skills:

vertex ai, gcp, python, modern NLP techniques, Google Cloud Platform, BigQuery, Cloud Functions, Cloud Run, CI/CD, version control, testing, debugging