AI Engineer – Generative AI & GCP
UST
Location
🇮🇳 India
Type
full_time
Salary
Undisclosed
Posted
1d ago
Job Description
We are looking for a highly skilled AI Engineer with strong expertise in Generative AI, Vertex AI, GCP, and Python to design, develop, and deploy scalable AI/ML solutions. The ideal candidate should have hands-on experience with LLM integrations, agentic AI workflows, RAG architectures, and MLOps practices within cloud-native environments.
Key Responsibilities
Model Development & Deployment • Design, train, fine-tune, and deploy scalable Machine Learning and Generative AI models using Vertex AI and the GCP ecosystem. • Build and manage end-to-end ML deployment pipelines using Vertex AI Pipelines, Model Registry, and Endpoints for real-time and batch inference. GenAI, LLM Integration & Agent Development • Integrate commercial and open-source LLM APIs into enterprise applications. • Design and develop agentic AI workflows using frameworks such as LangChain and LlamaIndex. • Implement prompt engineering strategies to improve reliability, accuracy, and security of model outputs. • Work with Model Context Protocol (MCP) integrations and AI orchestration frameworks. Advanced AI Architectures • Develop Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases. • Leverage transformer architectures and modern NLP techniques for semantic search and contextual AI solutions. • Design scalable, secure, and highly available cloud-native AI architectures. • Implement MLOps best practices including CI/CD pipelines, model monitoring, testing, and performance optimization. • Build and maintain automated data pipelines for model training, evaluation, and inference. Security & Governance • Ensure AI security, governance, compliance, and data privacy standards are followed. • Develop and implement AI Guardrails for responsible AI deployment. Mandatory Skills • Generative AI (GenAI) • Vertex AI • Google Cloud Platform (GCP) • Python • Agentic AI • Large Language Models (LLMs) • LangChain / LlamaIndex • RAG (Retrieval-Augmented Generation) • Vector Databases & Embeddings • MLOps & CI/CD • BigQuery, Cloud Storage, Cloud Functions / Cloud Run Preferred Skills • Google ADK • MCP (Model Context Protocol) • Transformer Architectures • NLP & Semantic Search • AI Security & Governance • Model Monitoring & Performance Tuning