AI Engineer (Data Pipelines & RAG)

Job Role- AI Engineer (Data Pipelines & RAG)

Job Type- Full-time

Work Mode- Remote(6 days working)

We are looking for a hands-on AI/Data Engineer (4–7 years) to build and scale data pipelines powering GenAI and agentic applications. You’ll architect data models, build ETL/ELT workflows, and integrate pipelines with RAG-based systems in a fast-paced startup environment.

What You’ll Do

Data Pipelines & Modeling

• Build scalable ETL/ELT pipelines (batch & streaming) using Python + Spark
• Automate ingestion from databases, APIs, files, SharePoint and other document sources
• Process & structure unstructured files (PDFs, tables, charts, drawings, etc.)
• Own chunking, indexing & embedding strategies for RAG/LLM use cases
• Design logical & physical data models, schema mappings & data dictionaries

GenAI & RAG Integration

• Feed real-time data into LLM prompts
• Build retrieval workflows for downstream agent/RAG systems in RE/Construction

Observability & Governance

• Implement monitoring, alerting & logging for pipeline reliability
• Apply IAM, Unity Catalog and other data privacy/security controls

CI/CD & Automation

• Use DevOps workflows with GitHub Actions/Azure DevOps/CircleCI
• Build reproducible infra using Terraform / ARM templates
• Use Prefect / Airflow for orchestration

What You’ll Need

• 5+ years in data engineering, with 1–2 years working on pipelines for unstructured data & RAG systems
• Strong Python + SQL, experience with dlt, DuckDB, DVC
• Azure cloud experience in production
• Experience with chunking/indexing strategies for RAG
• Strong Git/CI/CD workflows
• Familiarity with Prefect or equivalent
• Good to Have: MLflow, Docker/K8s, Computer Vision, agentic AI concepts, governance & privacy frameworks (GDPR)