Design, build, and deploy intelligent AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and edge computing
Job Summary
Design, build, and deploy intelligent AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and edge computing.
Work hands-on with cloud-native AI services, LLMOps pipelines, and enterprise-grade deployment patterns to solve business problems.
Create data strategy, ingestion, transformation, enrichment, validations, and quality checks via pipelines for AI ingestion, preprocessing, and governance.
Matching Summary
Design, build, and deploy intelligent AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and edge computing.
Skills & Requirements
Must-have
Generative AI/ML Engineer
LLM, RAG, agentic workflows
cloud-native AI services
LLMOps pipelines
enterprise-grade deployment
Python, Node.js, Rust
vector databases, embeddings
Nice-to-have
Generative agents with memory
Real-time AI streaming
Open-source GenAI contributions
ML model build, test, deploy
MCP, A2A protocol experience
Key Requirements
Experience in evaluating LLM applications
Experience building RAG-based and agentic AI solutions