Cloud-Based RAG Solutions Engineer

Cloud-Based RAG Solutions Engineer

Bangalore

13 LPA

Expected to have 5-8 years of experience in AI/ML solution design, with a focus on RAG pipeline implementation and cloud optimization, with at least 2-3 years of hands-on deployment experience in Azure environments.

1) Expertise in designing and implementing RAG-based LLM pipelines for document analysis and Q&A tasks .

2) Strong understanding of vector databases (e.g., FAISS, Pinecone) for semantic search and indexing.

3) Proven experience in integrating LLMs (e.g., GPT, BERT) into Azure-based AI workflows .

4) Hands-on experience deploying at least 2-3 PoCs of RAG-based LLM solutions on Azure.

5) Proficiency in Azure services such as Azure OpenAI, Cognitive Search, ML, and Synapse Analytics.

6) Knowledge of data engineering tools, including Azure Data Factory, Synapse, Data Lake, and Databricks.

7) Familiarity with cloud security frameworks and compliance standards for enterprise AI solutions.

8) Familiarity with advanced features like OCR integration, multi-modal processing, and real-time file uploads.

9) Strong experience in optimizing compute, storage, and networking configurations for AI solutions.

10) Hands-on experience with AI/ML frameworks such as TensorFlow and PyTorch, with MLOps knowledge.

11) Strong ability to configure, evaluate, and optimize scalable AI workflows while ensuring an optimal balance of accuracy and latency. Proficiency in performance benchmarking, ensuring efficiency for AI workflows in cloud ecosystems.

12) Familiarity with version control systems (Git, Bitbucket) and cloud-based deployment automation tools.

13) Experience conducting cloud security assessments, generating posture reports, and aligning with compliance standards.

14) Familiarity with Windows & Linux/Unix/Shell environments.

15) Strong oral and written communication skills.

16) Excellent analytical and problem-solving abilities.

17) Ability to work independently and collaboratively within cross-functional teams.

18) Certifications (preferred):

o Microsoft Certified: Azure AI Engineer Associate

o Relevant cloud security certifications (Azure, AWS, or GCP)

RAG, LLM and Azure cloud is mandatory

Virtual Mode

5- 8 Years