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)