Key Responsibilities:

- Design, develop, and maintain software solutions using Python.

- Build and operate RAG-based applications and systems.

- Develop and manage retrieval pipelines, embedding workflows, and LLM-backed generation.

- Integrate RAG solutions with enterprise data sources and applications.

- Work with Azure services, including Blob Storage and Azure Core Tools.

- Work with Databricks for data processing and engineering requirements.

- Integrate and work with connector ecosystems across platforms such as Confluence, SharePoint, ServiceNow, ServiceCloud, and Zendesk.

- Troubleshoot and optimize RAG systems for reliability, scalability, and performance.

- Collaborate with engineering and cross-functional teams to understand requirements and deliver effective solutions.

- Follow software engineering best practices for development, testing, deployment, and maintenance.

Must-Have Skills:

- Strong hands-on experience with Python.

- Hands-on experience building and operating RAG systems.

- Strong understanding of RAG components, including retrieval, embeddings, and LLM-backed generation.

- Experience developing and integrating AI/LLM-based applications.

- Familiarity with Azure services, particularly Blob Storage and Azure Core Tools.

- Working knowledge of Databricks.

- Experience working with enterprise data connectors or integration ecosystems.

- Strong problem-solving and analytical skills.