AI Data Platform Engineer – Knowledge Systems & RAG Infrastructure

About us:

Intuitive.Cloud is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solution and services companies supporting enterprise customers on a global scale. Intuitive is an "Engineering Company" delivering measurable value and key business outcomes.

Intuitive Superpowers:

- DataOps & AI/ML

- Cloud Native, AppSecOps, DevSecOps

- Cloud Migration & Transformation

- Cloud FinOps

- Cybersecurity (App/Data/Infra) & GRC

- SDx & Digital Workspace

We are proud to partner with some of the world's leading enterprises and serve 200+ customers across different industry verticals. We have achieved many milestones along the way, including being recognized as a top-10 fast-growth 150 IT company in the Americas by CRN in 2022 and being named one of America's fastest-growing private companies by INC 5000 in 2022. That’s not all! Even CIO Review awarded us as the Most Promising Cloud Migration Company and Artificial Intelligence Solutions Provider in 2022.

About the job:

Title – AI Engineer – Enterprise Automation & GenAI Applications

Start date: Immediate

Position Type: Full Time

Location: Remote across USA/ Canada/ India

Role Overview:

You will build the intelligent data foundation that powers our enterprise AI deployments. Your focus will be on ensuring the context, accuracy, and hyper-performance of the data layers feeding our large-scale applications, enabling contextual intelligence at an enterprise scale.

Key Responsibilities:

* Pipeline Engineering: Build and maintain scalable batch and real-time data ingestion and embedding pipelines.

* Infrastructure Management: Manage and optimize vector databases, data lakes, and lakehouses to support massive GenAI workloads.

* Performance Optimization: Continuously optimize retrieval performance, data quality, and data lineage to ensure accurate LLM grounding.

* Data Unification: Enable the seamless unification of structured and unstructured enterprise data for consumption by AI models.

Required Qualifications:

* Experience: 3+ years of dedicated experience in data engineering.

* Technical Stack: Strong proficiency with Spark, Databricks, Snowflake, Python, and SQL.

* System Design: Proven experience architecting robust APIs and highly available data pipelines for enterprise environments.